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Forget The ORM!

The document discusses the limitations of Object-Relational Mappers (ORMs) and their complexities in managing data, highlighting issues like the 'object-relational impedance mismatch.' It suggests alternatives through non-traditional databases, known as NoSQL, which include document and object storage options. The document also reviews various NoSQL solutions such as CouchDB, MongoDB, and Neo4j, outlining their functionalities and unique features.

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Forget the ORM! Persistent data with Non-traditional Databases By Randal L. Schwartz, Stonehenge Consulting Services, Inc. <merlyn@stonehenge.com> http://www.stonehenge.com/merlyn/ version 1.2 at 13 April 2010
What we are covering
What we are covering • What is an Object-Relational-Mapper?
What we are covering • What is an Object-Relational-Mapper? • Why is it evil?
What we are covering • What is an Object-Relational-Mapper? • Why is it evil? • What are the alternatives?
Brief review of ORMs
Brief review of ORMs • Objects in memory
Brief review of ORMs • Objects in memory • Tables in RDBMS
Brief review of ORMs • Objects in memory • Tables in RDBMS • Load objects from tables
Brief review of ORMs • Objects in memory • Tables in RDBMS • Load objects from tables • Store objects (and changes) back to tables
Brief review of ORMs • Objects in memory • Tables in RDBMS • Load objects from tables • Store objects (and changes) back to tables • Typically mapped one attribute per column
Brief review of ORMs • Objects in memory • Tables in RDBMS • Load objects from tables • Store objects (and changes) back to tables • Typically mapped one attribute per column • Occasionally more complex mappings
But things change
But things change • Object attributes get updated
But things change • Object attributes get updated • New objects get created
But things change • Object attributes get updated • New objects get created • Need to map that back to the RDB
But things change • Object attributes get updated • New objects get created • Need to map that back to the RDB • Updates often require custom SQL
But things change • Object attributes get updated • New objects get created • Need to map that back to the RDB • Updates often require custom SQL • Or live with updating more than needed
But things change • Object attributes get updated • New objects get created • Need to map that back to the RDB • Updates often require custom SQL • Or live with updating more than needed • Detecting what has changed can be hard
One-to-many messes
One-to-many messes • Messy when an attribute is a reference
One-to-many messes • Messy when an attribute is a reference • Or a non-DB data type, like a set
One-to-many messes • Messy when an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins
One-to-many messes • Messy when an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins • Left joins to get child rows
One-to-many messes • Messy when an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins • Left joins to get child rows • Or multiple trips to get joined data
One-to-many messes • Messy when an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins • Left joins to get child rows • Or multiple trips to get joined data • Either way, expensive
Why this is bad
Why this is bad • If your car were an ORM...
Why this is bad • If your car were an ORM... • Reduce it to parts each night in garage
Why this is bad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning
Why this is bad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century?
Why this is bad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century? • Most ORMs generate the SQL on the fly
Why this is bad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century? • Most ORMs generate the SQL on the fly • Recompiling text on each hit?
Why this is bad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century? • Most ORMs generate the SQL on the fly • Recompiling text on each hit? • Often called the “object relational impedence mismatch”
How to solve it
How to solve it • Rectangles don’t fit today’s data
How to solve it • Rectangles don’t fit today’s data • Solution: Don’t store rectangles
How to solve it • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions
How to solve it • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options:
How to solve it • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options: • Document storage (typically JSON)
How to solve it • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options: • Document storage (typically JSON) • Object storage
How to solve it • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options: • Document storage (typically JSON) • Object storage • (Generally) not possible if other apps still need the data as RDB
Dropping ACID
Dropping ACID • Automicity, Consistency, Isolation, Durability
Dropping ACID • Automicity, Consistency, Isolation, Durability • Often expressed through transactions
Dropping ACID • Automicity, Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID
Dropping ACID • Automicity, Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID • But atomic within a single doc update
Dropping ACID • Automicity, Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID • But atomic within a single doc update • Thus, think about your “schema” carefully
Dropping ACID • Automicity, Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID • But atomic within a single doc update • Thus, think about your “schema” carefully • Ensure single doc update suffices
Eric Brewer’s CAP
Eric Brewer’s CAP • Consistency
Eric Brewer’s CAP • Consistency • All working, or not working
Eric Brewer’s CAP • Consistency • All working, or not working • Yes, this is the “A” in ACID
Eric Brewer’s CAP • Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability
Eric Brewer’s CAP • Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running?
Eric Brewer’s CAP • Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running? • Partition Tolerance
Eric Brewer’s CAP • Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running? • Partition Tolerance • Can parts of it go offline safely?
Eric Brewer’s CAP • Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running? • Partition Tolerance • Can parts of it go offline safely? • .... Pick any two
Current solutions
Current solutions • Document store
Current solutions • Document store • Graph
Current solutions • Document store • Graph • Key/Value in RAM/Disk
Current solutions • Document store • Graph • Key/Value in RAM/Disk • Key/Value on Disk
Current solutions • Document store • Graph • Key/Value in RAM/Disk • Key/Value on Disk • Tabular
Current solutions • Document store • Graph • Key/Value in RAM/Disk • Key/Value on Disk • Tabular • Object Database
Document Store
Document Store • CouchDB
Document Store • CouchDB • MongoDB
Document Store • CouchDB • MongoDB • Apache Jackrabbit
Document Store • CouchDB • MongoDB • Apache Jackrabbit • XML Databases
Document Store • CouchDB • MongoDB • Apache Jackrabbit • XML Databases • MarkLogic Server
Document Store • CouchDB • MongoDB • Apache Jackrabbit • XML Databases • MarkLogic Server • GemFire
Document Store • CouchDB • MongoDB • Apache Jackrabbit • XML Databases • MarkLogic Server • GemFire • eXist
CouchDB
CouchDB • Open source (Erlang, Apache 2.0)
CouchDB • Open source (Erlang, Apache 2.0) • Stores JSON documents
CouchDB • Open source (Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing
CouchDB • Open source (Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views”
CouchDB • Open source (Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions
CouchDB • Open source (Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions • Scales with map/reduce
CouchDB • Open source (Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions • Scales with map/reduce • RESTful API
CouchDB • Open source (Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions • Scales with map/reduce • RESTful API • FLOSS Weekly #36
MongoDB
MongoDB • Open source (C++, GNU AGPL3)
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication • Auto-sharding
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication • Auto-sharding • Bindings for many languages
MongoDB • Open source (C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication • Auto-sharding • Bindings for many languages • FLOSS Weekly #105
Apache Jackrabbit
Apache Jackrabbit • Open source (Java, Apache 2.0)
Apache Jackrabbit • Open source (Java, Apache 2.0) • XML content on disk
Apache Jackrabbit • Open source (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API
Apache Jackrabbit • Open source (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search
Apache Jackrabbit • Open source (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search • Versioning, transactions, observation
Apache Jackrabbit • Open source (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search • Versioning, transactions, observation • Authentication
Apache Jackrabbit • Open source (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search • Versioning, transactions, observation • Authentication • Object persistence using Object Content Manager
MarkLogic Server
MarkLogic Server • Not open-source
MarkLogic Server • Not open-source • XML database
MarkLogic Server • Not open-source • XML database • Implements XQuery
MarkLogic Server • Not open-source • XML database • Implements XQuery • Full-text and structured search
MarkLogic Server • Not open-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches
MarkLogic Server • Not open-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches • In heavy use by their customers
MarkLogic Server • Not open-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches • In heavy use by their customers • Scalable to “hundreds of terabytes”
MarkLogic Server • Not open-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches • In heavy use by their customers • Scalable to “hundreds of terabytes” • Both native and RESTful APIs
GemFire
GemFire • Not open-source
GemFire • Not open-source • Mostly-in-memory distributed object cache
GemFire • Not open-source • Mostly-in-memory distributed object cache • Change notification
GemFire • Not open-source • Mostly-in-memory distributed object cache • Change notification • Highly available
GemFire • Not open-source • Mostly-in-memory distributed object cache • Change notification • Highly available • Object Query Language compatible
GemFire • Not open-source • Mostly-in-memory distributed object cache • Change notification • Highly available • Object Query Language compatible • Native Java/C++/C# objects
GemFire • Not open-source • Mostly-in-memory distributed object cache • Change notification • Highly available • Object Query Language compatible • Native Java/C++/C# objects • Persistence to file system, databases, etc
eXist
eXist • Open source (Java, LGPL)
eXist • Open source (Java, LGPL) • Native XML queries
eXist • Open source (Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate
eXist • Open source (Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP
eXist • Open source (Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps!
eXist • Open source (Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps! • Used by large installations
eXist • Open source (Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps! • Used by large installations • US State Department (history.state.gov)
eXist • Open source (Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps! • Used by large installations • US State Department (history.state.gov) • FLOSS Weekly #97
Graph
Graph • InfoGrid
Graph • InfoGrid • Neo4J
Graph • InfoGrid • Neo4J • AllegroGraph
InfoGrid
InfoGrid • Open source (Java, AGPL3)
InfoGrid • Open source (Java, AGPL3) • GraphDatabase stores nodes and edges
InfoGrid • Open source (Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained
InfoGrid • Open source (Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained • NetMeshBase - distributed knowledge
InfoGrid • Open source (Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained • NetMeshBase - distributed knowledge • API in front of other SQL and NoSQL DBs
InfoGrid • Open source (Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained • NetMeshBase - distributed knowledge • API in front of other SQL and NoSQL DBs • Includes components for authentication
Neo4j
Neo4j • Open source (Java, AGPL3)
Neo4j • Open source (Java, AGPL3) • Commercial support/version available
Neo4j • Open source (Java, AGPL3) • Commercial support/version available • Java objects on disk
Neo4j • Open source (Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional
Neo4j • Open source (Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional • Scalable (several billion nodes on single machine)
Neo4j • Open source (Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional • Scalable (several billion nodes on single machine) • Small footprint (JAR under 500KB)
Neo4j • Open source (Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional • Scalable (several billion nodes on single machine) • Small footprint (JAR under 500KB) • RDF mappings
AllegroGraph
AllegroGraph • Free versions (not open source)
AllegroGraph • Free versions (not open source) • Holds Resource Description Frameworks
AllegroGraph • Free versions (not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc)
AllegroGraph • Free versions (not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages
AllegroGraph • Free versions (not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development
AllegroGraph • Free versions (not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development • In use by FLOSS/commercial/government
AllegroGraph • Free versions (not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development • In use by FLOSS/commercial/government • Queries with SPARQL
AllegroGraph • Free versions (not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development • In use by FLOSS/commercial/government • Queries with SPARQL • ... Protocol and RDF Query Language
Key/Value in RAM/Disk
Key/Value in RAM/Disk • memcached
Key/Value in RAM/Disk • memcached • Redis
Memcached
Memcached • Open source (C, BSD)
Memcached • Open source (C, BSD) • LRU cache (data may be lost)
Memcached • Open source (C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal
Memcached • Open source (C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites
Memcached • Open source (C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage
Memcached • Open source (C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage • Keys up to 120 bytes, values 1 MB
Memcached • Open source (C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage • Keys up to 120 bytes, values 1 MB • Clientside horizontal scaling
Memcached • Open source (C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage • Keys up to 120 bytes, values 1 MB • Clientside horizontal scaling • Can also store on disk (memcachedb)
Redis
Redis • Open source (C, BSD)
Redis • Open source (C, BSD) • Development funded by VMWare
Redis • Open source (C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair)
Redis • Open source (C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes
Redis • Open source (C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported
Redis • Open source (C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available
Redis • Open source (C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available • Used by many big sites
Redis • Open source (C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available • Used by many big sites • Github, Craigslist, Engine Yard, Guardian
Redis • Open source (C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available • Used by many big sites • Github, Craigslist, Engine Yard, Guardian • Can also store on disk
Key/Value on Disk
Key/Value on Disk • Amazon SimpleDB
Key/Value on Disk • Amazon SimpleDB • Berkeley DB
Key/Value on Disk • Amazon SimpleDB • Berkeley DB • Tokyo Cabinet
Key/Value on Disk • Amazon SimpleDB • Berkeley DB • Tokyo Cabinet • Cassandra
Key/Value on Disk • Amazon SimpleDB • Berkeley DB • Tokyo Cabinet • Cassandra • GT.M
Amazon SimpleDB
Amazon SimpleDB • Built by Amazon in Erlang
Amazon SimpleDB • Built by Amazon in Erlang • Supports EC2 applications
Amazon SimpleDB • Built by Amazon in Erlang • Supports EC2 applications • Highly scalable
Amazon SimpleDB • Built by Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency
Amazon SimpleDB • Built by Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency • Items have query-able attributes
Amazon SimpleDB • Built by Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency • Items have query-able attributes • No text search
Amazon SimpleDB • Built by Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency • Items have query-able attributes • No text search • Build your own indexes
Berkeley DB
Berkeley DB • Open source (C, Sleepycat)
Berkeley DB • Open source (C, Sleepycat) • Enhancement of original DBM from AT&T
Berkeley DB • Open source (C, Sleepycat) • Enhancement of original DBM from AT&T • Key/value pairs in various storage formats
Berkeley DB • Open source (C, Sleepycat) • Enhancement of original DBM from AT&T • Key/value pairs in various storage formats • Transactional locking, HA features
Berkeley DB • Open source (C, Sleepycat) • Enhancement of original DBM from AT&T • Key/value pairs in various storage formats • Transactional locking, HA features • Widely used
Tokyo Cabinet
Tokyo Cabinet • Open source (C, LGPL)
Tokyo Cabinet • Open source (C, LGPL) • Successor to GDBM and QDBM
Tokyo Cabinet • Open source (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed
Tokyo Cabinet • Open source (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs
Tokyo Cabinet • Open source (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies
Tokyo Cabinet • Open source (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies • Multiple client language interfaces
Tokyo Cabinet • Open source (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies • Multiple client language interfaces • Local storage only: no network interface
Tokyo Cabinet • Open source (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies • Multiple client language interfaces • Local storage only: no network interface • But see Tokyo Tyrant
Cassandra
Cassandra • Open source (Java, Apache 2)
Cassandra • Open source (Java, Apache 2) • Originally developed at Facebook
Cassandra • Open source (Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage
Cassandra • Open source (Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication
Cassandra • Open source (Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication • Used by Facebook, Digg, Twitter, Rackspace
Cassandra • Open source (Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication • Used by Facebook, Digg, Twitter, Rackspace • Eventually consistent
Cassandra • Open source (Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication • Used by Facebook, Digg, Twitter, Rackspace • Eventually consistent • Queries can ask “majority” or “all”
GT.M
GT.M • Open Source (Mumps, GPL)
GT.M • Open Source (Mumps, GPL) • Commercial support from Fidelity
GT.M • Open Source (Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs
GT.M • Open Source (Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs • Transactions via optimistic concurrency
GT.M • Open Source (Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs • Transactions via optimistic concurrency • Everything you read must be unchanged
GT.M • Open Source (Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs • Transactions via optimistic concurrency • Everything you read must be unchanged • Mumps-to-C-to-Mumps APIs
Tabular
Tabular • Mnesia
Tabular • Mnesia • Hbase
Tabular • Mnesia • Hbase • Hypertable
Mnesia
Mnesia • Open source (Erlang, Erlang license)
Mnesia • Open source (Erlang, Erlang license) • Key/value pairs
Mnesia • Open source (Erlang, Erlang license) • Key/value pairs • Value is any Erlang datatype
Mnesia • Open source (Erlang, Erlang license) • Key/value pairs • Value is any Erlang datatype • Live reconfiguration
Mnesia • Open source (Erlang, Erlang license) • Key/value pairs • Value is any Erlang datatype • Live reconfiguration • Supports transactions and distribution
Hbase
Hbase • Open source (Java, Apache 2)
Hbase • Open source (Java, Apache 2) • Mimics Google’s “BigTable”
Hbase • Open source (Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards
Hbase • Open source (Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards • Runs on Hadoop Distributed File System
Hbase • Open source (Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards • Runs on Hadoop Distributed File System • Java, REST, Thrift APIs
Hbase • Open source (Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards • Runs on Hadoop Distributed File System • Java, REST, Thrift APIs • Might be the DB behind Bing
Hypertable
Hypertable • Open source (C++, GPL 2)
Hypertable • Open source (C++, GPL 2) • Yet another BigTable clone
Hypertable • Open source (C++, GPL 2) • Yet another BigTable clone • Designed for highly scalable data storage
Object database
Object database • Db4o
Object database • Db4o • InterSystems Cache
Object database • Db4o • InterSystems Cache • ZODB
Object database • Db4o • InterSystems Cache • ZODB • GemStone/S
Object database • Db4o • InterSystems Cache • ZODB • GemStone/S • Magma
Db4o
Db4o • Open source (Java/C#, GPL)
Db4o • Open source (Java/C#, GPL) • Commercial license/support available
Db4o • Open source (Java/C#, GPL) • Commercial license/support available • Supports object persistence
Db4o • Open source (Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net
Db4o • Open source (Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS
Db4o • Open source (Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS • Supports class migration
Db4o • Open source (Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS • Supports class migration • ... if you provide the code
Db4o • Open source (Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS • Supports class migration • ... if you provide the code • Large community
InterSystems Cache
InterSystems Cache • Commercial
InterSystems Cache • Commercial • “World’s fastest object database”
InterSystems Cache • Commercial • “World’s fastest object database” • Cross-platform
InterSystems Cache • Commercial • “World’s fastest object database” • Cross-platform • Persistence of multidimensional arrays
InterSystems Cache • Commercial • “World’s fastest object database” • Cross-platform • Persistence of multidimensional arrays • Similar to MUMPS/Pick data
InterSystems Cache • Commercial • “World’s fastest object database” • Cross-platform • Persistence of multidimensional arrays • Similar to MUMPS/Pick data • Can be embedded in web pages
ZODB
ZODB • Open source (Python, Zope license)
ZODB • Open source (Python, Zope license) • “Seamless object persistence”
ZODB • Open source (Python, Zope license) • “Seamless object persistence” • Transactions, MVCC
ZODB • Open source (Python, Zope license) • “Seamless object persistence” • Transactions, MVCC • Scaling across a network
ZODB • Open source (Python, Zope license) • “Seamless object persistence” • Transactions, MVCC • Scaling across a network • Widely used
ZODB • Open source (Python, Zope license) • “Seamless object persistence” • Transactions, MVCC • Scaling across a network • Widely used • Zope Replication Services (commercial)
GemStone/S
GemStone/S • Commercial (free license for small apps)
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist”
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist” • Includes Java interface
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic • JPM’s Kapital created the financial crisis :)
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic • JPM’s Kapital created the financial crisis :) • Integrates with Seaside
GemStone/S • Commercial (free license for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic • JPM’s Kapital created the financial crisis :) • Integrates with Seaside • Web apps with transparent persistence
Magma
Magma • Open source (Squeak Smalltalk, MIT)
Magma • Open source (Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence
Magma • Open source (Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S”
Magma • Open source (Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model
Magma • Open source (Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model • HA mode (multiple slaves ready for master)
Magma • Open source (Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model • HA mode (multiple slaves ready for master) • Transaction-based (commit/rollback)
Magma • Open source (Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model • HA mode (multiple slaves ready for master) • Transaction-based (commit/rollback) • Works nicely with Seaside
In summary
In summary • Lots of ways to not use SQL
In summary • Lots of ways to not use SQL • Many open source
In summary • Lots of ways to not use SQL • Many open source • Many commercially supported
In summary • Lots of ways to not use SQL • Many open source • Many commercially supported • Don’t assume you need an ORM!
How to contact me
How to contact me • Email: merlyn@stonehenge.com
How to contact me • Email: merlyn@stonehenge.com • Twitter: @merlyn
How to contact me • Email: merlyn@stonehenge.com • Twitter: @merlyn • Website: www.stonehenge.com
How to contact me • Email: merlyn@stonehenge.com • Twitter: @merlyn • Website: www.stonehenge.com • Phone: +1 503 777 0095

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Forget The ORM!

  • 1.
    Forget the ORM! Persistent data with Non-traditional Databases By Randal L. Schwartz, Stonehenge Consulting Services, Inc. <merlyn@stonehenge.com> http://www.stonehenge.com/merlyn/ version 1.2 at 13 April 2010
  • 2.
    What we arecovering
  • 3.
    What we arecovering • What is an Object-Relational-Mapper?
  • 4.
    What we arecovering • What is an Object-Relational-Mapper? • Why is it evil?
  • 5.
    What we arecovering • What is an Object-Relational-Mapper? • Why is it evil? • What are the alternatives?
  • 6.
  • 7.
    Brief review ofORMs • Objects in memory
  • 8.
    Brief review ofORMs • Objects in memory • Tables in RDBMS
  • 9.
    Brief review ofORMs • Objects in memory • Tables in RDBMS • Load objects from tables
  • 10.
    Brief review ofORMs • Objects in memory • Tables in RDBMS • Load objects from tables • Store objects (and changes) back to tables
  • 11.
    Brief review ofORMs • Objects in memory • Tables in RDBMS • Load objects from tables • Store objects (and changes) back to tables • Typically mapped one attribute per column
  • 12.
    Brief review ofORMs • Objects in memory • Tables in RDBMS • Load objects from tables • Store objects (and changes) back to tables • Typically mapped one attribute per column • Occasionally more complex mappings
  • 13.
  • 14.
    But things change •Object attributes get updated
  • 15.
    But things change •Object attributes get updated • New objects get created
  • 16.
    But things change •Object attributes get updated • New objects get created • Need to map that back to the RDB
  • 17.
    But things change •Object attributes get updated • New objects get created • Need to map that back to the RDB • Updates often require custom SQL
  • 18.
    But things change •Object attributes get updated • New objects get created • Need to map that back to the RDB • Updates often require custom SQL • Or live with updating more than needed
  • 19.
    But things change •Object attributes get updated • New objects get created • Need to map that back to the RDB • Updates often require custom SQL • Or live with updating more than needed • Detecting what has changed can be hard
  • 20.
  • 21.
    One-to-many messes • Messywhen an attribute is a reference
  • 22.
    One-to-many messes • Messywhen an attribute is a reference • Or a non-DB data type, like a set
  • 23.
    One-to-many messes • Messywhen an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins
  • 24.
    One-to-many messes • Messywhen an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins • Left joins to get child rows
  • 25.
    One-to-many messes • Messywhen an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins • Left joins to get child rows • Or multiple trips to get joined data
  • 26.
    One-to-many messes • Messywhen an attribute is a reference • Or a non-DB data type, like a set • Mapping involves joins • Left joins to get child rows • Or multiple trips to get joined data • Either way, expensive
  • 27.
  • 28.
    Why this isbad • If your car were an ORM...
  • 29.
    Why this isbad • If your car were an ORM... • Reduce it to parts each night in garage
  • 30.
    Why this isbad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning
  • 31.
    Why this isbad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century?
  • 32.
    Why this isbad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century? • Most ORMs generate the SQL on the fly
  • 33.
    Why this isbad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century? • Most ORMs generate the SQL on the fly • Recompiling text on each hit?
  • 34.
    Why this isbad • If your car were an ORM... • Reduce it to parts each night in garage • Rebuild it each morning • Is this sane in the 21st century? • Most ORMs generate the SQL on the fly • Recompiling text on each hit? • Often called the “object relational impedence mismatch”
  • 35.
  • 36.
    How to solveit • Rectangles don’t fit today’s data
  • 37.
    How to solveit • Rectangles don’t fit today’s data • Solution: Don’t store rectangles
  • 38.
    How to solveit • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions
  • 39.
    How to solveit • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options:
  • 40.
    How to solveit • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options: • Document storage (typically JSON)
  • 41.
    How to solveit • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options: • Document storage (typically JSON) • Object storage
  • 42.
    How to solveit • Rectangles don’t fit today’s data • Solution: Don’t store rectangles • Also known as “NoSQL” solutions • Two main options: • Document storage (typically JSON) • Object storage • (Generally) not possible if other apps still need the data as RDB
  • 43.
  • 44.
    Dropping ACID • Automicity,Consistency, Isolation, Durability
  • 45.
    Dropping ACID • Automicity,Consistency, Isolation, Durability • Often expressed through transactions
  • 46.
    Dropping ACID • Automicity,Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID
  • 47.
    Dropping ACID • Automicity,Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID • But atomic within a single doc update
  • 48.
    Dropping ACID • Automicity,Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID • But atomic within a single doc update • Thus, think about your “schema” carefully
  • 49.
    Dropping ACID • Automicity,Consistency, Isolation, Durability • Often expressed through transactions • Most NoSQL offer no multi-update ACID • But atomic within a single doc update • Thus, think about your “schema” carefully • Ensure single doc update suffices
  • 50.
  • 51.
  • 52.
    Eric Brewer’s CAP •Consistency • All working, or not working
  • 53.
    Eric Brewer’s CAP •Consistency • All working, or not working • Yes, this is the “A” in ACID
  • 54.
    Eric Brewer’s CAP •Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability
  • 55.
    Eric Brewer’s CAP •Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running?
  • 56.
    Eric Brewer’s CAP •Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running? • Partition Tolerance
  • 57.
    Eric Brewer’s CAP •Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running? • Partition Tolerance • Can parts of it go offline safely?
  • 58.
    Eric Brewer’s CAP •Consistency • All working, or not working • Yes, this is the “A” in ACID • Availability • Is the service up and running? • Partition Tolerance • Can parts of it go offline safely? • .... Pick any two
  • 59.
  • 60.
  • 61.
  • 62.
    Current solutions • Documentstore • Graph • Key/Value in RAM/Disk
  • 63.
    Current solutions • Documentstore • Graph • Key/Value in RAM/Disk • Key/Value on Disk
  • 64.
    Current solutions • Documentstore • Graph • Key/Value in RAM/Disk • Key/Value on Disk • Tabular
  • 65.
    Current solutions • Documentstore • Graph • Key/Value in RAM/Disk • Key/Value on Disk • Tabular • Object Database
  • 66.
  • 67.
  • 68.
  • 69.
    Document Store • CouchDB •MongoDB • Apache Jackrabbit
  • 70.
    Document Store • CouchDB •MongoDB • Apache Jackrabbit • XML Databases
  • 71.
    Document Store • CouchDB •MongoDB • Apache Jackrabbit • XML Databases • MarkLogic Server
  • 72.
    Document Store • CouchDB •MongoDB • Apache Jackrabbit • XML Databases • MarkLogic Server • GemFire
  • 73.
    Document Store • CouchDB •MongoDB • Apache Jackrabbit • XML Databases • MarkLogic Server • GemFire • eXist
  • 74.
  • 75.
    CouchDB • Open source(Erlang, Apache 2.0)
  • 76.
    CouchDB • Open source(Erlang, Apache 2.0) • Stores JSON documents
  • 77.
    CouchDB • Open source(Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing
  • 78.
    CouchDB • Open source(Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views”
  • 79.
    CouchDB • Open source(Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions
  • 80.
    CouchDB • Open source(Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions • Scales with map/reduce
  • 81.
    CouchDB • Open source(Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions • Scales with map/reduce • RESTful API
  • 82.
    CouchDB • Open source(Erlang, Apache 2.0) • Stores JSON documents • Uses SpiderMonkey for processing • Provides “views” • Aggregate functions • Scales with map/reduce • RESTful API • FLOSS Weekly #36
  • 83.
  • 84.
    MongoDB • Open source(C++, GNU AGPL3)
  • 85.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON
  • 86.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce
  • 87.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell
  • 88.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates
  • 89.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication
  • 90.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication • Auto-sharding
  • 91.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication • Auto-sharding • Bindings for many languages
  • 92.
    MongoDB • Open source(C++, GNU AGPL3) • Wire/Storage protocol is BSON • Embedded JavaScript for map/reduce • Interactive JavaScript shell • In-place updates • Replication • Auto-sharding • Bindings for many languages • FLOSS Weekly #105
  • 93.
  • 94.
    Apache Jackrabbit • Opensource (Java, Apache 2.0)
  • 95.
    Apache Jackrabbit • Opensource (Java, Apache 2.0) • XML content on disk
  • 96.
    Apache Jackrabbit • Opensource (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API
  • 97.
    Apache Jackrabbit • Opensource (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search
  • 98.
    Apache Jackrabbit • Opensource (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search • Versioning, transactions, observation
  • 99.
    Apache Jackrabbit • Opensource (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search • Versioning, transactions, observation • Authentication
  • 100.
    Apache Jackrabbit • Opensource (Java, Apache 2.0) • XML content on disk • Implements Java Content Repository API • Full text and XPath search • Versioning, transactions, observation • Authentication • Object persistence using Object Content Manager
  • 101.
  • 102.
  • 103.
    MarkLogic Server • Notopen-source • XML database
  • 104.
    MarkLogic Server • Notopen-source • XML database • Implements XQuery
  • 105.
    MarkLogic Server • Notopen-source • XML database • Implements XQuery • Full-text and structured search
  • 106.
    MarkLogic Server • Notopen-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches
  • 107.
    MarkLogic Server • Notopen-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches • In heavy use by their customers
  • 108.
    MarkLogic Server • Notopen-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches • In heavy use by their customers • Scalable to “hundreds of terabytes”
  • 109.
    MarkLogic Server • Notopen-source • XML database • Implements XQuery • Full-text and structured search • Native geospatial searches • In heavy use by their customers • Scalable to “hundreds of terabytes” • Both native and RESTful APIs
  • 110.
  • 111.
  • 112.
    GemFire • Not open-source •Mostly-in-memory distributed object cache
  • 113.
    GemFire • Not open-source •Mostly-in-memory distributed object cache • Change notification
  • 114.
    GemFire • Not open-source •Mostly-in-memory distributed object cache • Change notification • Highly available
  • 115.
    GemFire • Not open-source •Mostly-in-memory distributed object cache • Change notification • Highly available • Object Query Language compatible
  • 116.
    GemFire • Not open-source •Mostly-in-memory distributed object cache • Change notification • Highly available • Object Query Language compatible • Native Java/C++/C# objects
  • 117.
    GemFire • Not open-source •Mostly-in-memory distributed object cache • Change notification • Highly available • Object Query Language compatible • Native Java/C++/C# objects • Persistence to file system, databases, etc
  • 118.
  • 119.
  • 120.
    eXist • Open source(Java, LGPL) • Native XML queries
  • 121.
    eXist • Open source(Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate
  • 122.
    eXist • Open source(Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP
  • 123.
    eXist • Open source(Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps!
  • 124.
    eXist • Open source(Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps! • Used by large installations
  • 125.
    eXist • Open source(Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps! • Used by large installations • US State Department (history.state.gov)
  • 126.
    eXist • Open source(Java, LGPL) • Native XML queries • XQuery, XPath, XSLT, XUpdate • Rich APIs: REST, WebDAV, SOAP • Can serve entire webapps! • Used by large installations • US State Department (history.state.gov) • FLOSS Weekly #97
  • 127.
  • 128.
  • 129.
  • 130.
  • 131.
  • 132.
  • 133.
    InfoGrid • Open source(Java, AGPL3) • GraphDatabase stores nodes and edges
  • 134.
    InfoGrid • Open source(Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained
  • 135.
    InfoGrid • Open source(Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained • NetMeshBase - distributed knowledge
  • 136.
    InfoGrid • Open source(Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained • NetMeshBase - distributed knowledge • API in front of other SQL and NoSQL DBs
  • 137.
    InfoGrid • Open source(Java, AGPL3) • GraphDatabase stores nodes and edges • MeshBase - self contained • NetMeshBase - distributed knowledge • API in front of other SQL and NoSQL DBs • Includes components for authentication
  • 138.
  • 139.
    Neo4j • Open source(Java, AGPL3)
  • 140.
    Neo4j • Open source(Java, AGPL3) • Commercial support/version available
  • 141.
    Neo4j • Open source(Java, AGPL3) • Commercial support/version available • Java objects on disk
  • 142.
    Neo4j • Open source(Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional
  • 143.
    Neo4j • Open source(Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional • Scalable (several billion nodes on single machine)
  • 144.
    Neo4j • Open source(Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional • Scalable (several billion nodes on single machine) • Small footprint (JAR under 500KB)
  • 145.
    Neo4j • Open source(Java, AGPL3) • Commercial support/version available • Java objects on disk • Transactional • Scalable (several billion nodes on single machine) • Small footprint (JAR under 500KB) • RDF mappings
  • 146.
  • 147.
  • 148.
    AllegroGraph • Free versions(not open source) • Holds Resource Description Frameworks
  • 149.
    AllegroGraph • Free versions(not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc)
  • 150.
    AllegroGraph • Free versions(not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages
  • 151.
    AllegroGraph • Free versions(not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development
  • 152.
    AllegroGraph • Free versions(not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development • In use by FLOSS/commercial/government
  • 153.
    AllegroGraph • Free versions(not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development • In use by FLOSS/commercial/government • Queries with SPARQL
  • 154.
    AllegroGraph • Free versions(not open source) • Holds Resource Description Frameworks • From Franz, Inc (Franz Lisp, etc) • Interfaces in many common languages • Active development • In use by FLOSS/commercial/government • Queries with SPARQL • ... Protocol and RDF Query Language
  • 155.
  • 156.
  • 157.
    Key/Value in RAM/Disk •memcached • Redis
  • 158.
  • 159.
  • 160.
    Memcached • Open source(C, BSD) • LRU cache (data may be lost)
  • 161.
    Memcached • Open source(C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal
  • 162.
    Memcached • Open source(C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites
  • 163.
    Memcached • Open source(C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage
  • 164.
    Memcached • Open source(C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage • Keys up to 120 bytes, values 1 MB
  • 165.
    Memcached • Open source(C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage • Keys up to 120 bytes, values 1 MB • Clientside horizontal scaling
  • 166.
    Memcached • Open source(C, BSD) • LRU cache (data may be lost) • Developed for LiveJournal • used by many large sites • Simple key/value storage • Keys up to 120 bytes, values 1 MB • Clientside horizontal scaling • Can also store on disk (memcachedb)
  • 167.
  • 168.
  • 169.
    Redis • Open source(C, BSD) • Development funded by VMWare
  • 170.
    Redis • Open source(C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair)
  • 171.
    Redis • Open source(C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes
  • 172.
    Redis • Open source(C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported
  • 173.
    Redis • Open source(C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available
  • 174.
    Redis • Open source(C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available • Used by many big sites
  • 175.
    Redis • Open source(C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available • Used by many big sites • Github, Craigslist, Engine Yard, Guardian
  • 176.
    Redis • Open source(C, BSD) • Development funded by VMWare • Similar to Memcached (key/value pair) • Values can be lists, sets, hashes • Master/slave replication supported • Many client languages available • Used by many big sites • Github, Craigslist, Engine Yard, Guardian • Can also store on disk
  • 177.
  • 178.
    Key/Value on Disk •Amazon SimpleDB
  • 179.
    Key/Value on Disk •Amazon SimpleDB • Berkeley DB
  • 180.
    Key/Value on Disk •Amazon SimpleDB • Berkeley DB • Tokyo Cabinet
  • 181.
    Key/Value on Disk •Amazon SimpleDB • Berkeley DB • Tokyo Cabinet • Cassandra
  • 182.
    Key/Value on Disk •Amazon SimpleDB • Berkeley DB • Tokyo Cabinet • Cassandra • GT.M
  • 183.
  • 184.
    Amazon SimpleDB • Builtby Amazon in Erlang
  • 185.
    Amazon SimpleDB • Builtby Amazon in Erlang • Supports EC2 applications
  • 186.
    Amazon SimpleDB • Builtby Amazon in Erlang • Supports EC2 applications • Highly scalable
  • 187.
    Amazon SimpleDB • Builtby Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency
  • 188.
    Amazon SimpleDB • Builtby Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency • Items have query-able attributes
  • 189.
    Amazon SimpleDB • Builtby Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency • Items have query-able attributes • No text search
  • 190.
    Amazon SimpleDB • Builtby Amazon in Erlang • Supports EC2 applications • Highly scalable • “Eventual” Consistency • Items have query-able attributes • No text search • Build your own indexes
  • 191.
  • 192.
    Berkeley DB • Opensource (C, Sleepycat)
  • 193.
    Berkeley DB • Opensource (C, Sleepycat) • Enhancement of original DBM from AT&T
  • 194.
    Berkeley DB • Opensource (C, Sleepycat) • Enhancement of original DBM from AT&T • Key/value pairs in various storage formats
  • 195.
    Berkeley DB • Opensource (C, Sleepycat) • Enhancement of original DBM from AT&T • Key/value pairs in various storage formats • Transactional locking, HA features
  • 196.
    Berkeley DB • Opensource (C, Sleepycat) • Enhancement of original DBM from AT&T • Key/value pairs in various storage formats • Transactional locking, HA features • Widely used
  • 197.
  • 198.
    Tokyo Cabinet • Opensource (C, LGPL)
  • 199.
    Tokyo Cabinet • Opensource (C, LGPL) • Successor to GDBM and QDBM
  • 200.
    Tokyo Cabinet • Opensource (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed
  • 201.
    Tokyo Cabinet • Opensource (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs
  • 202.
    Tokyo Cabinet • Opensource (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies
  • 203.
    Tokyo Cabinet • Opensource (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies • Multiple client language interfaces
  • 204.
    Tokyo Cabinet • Opensource (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies • Multiple client language interfaces • Local storage only: no network interface
  • 205.
    Tokyo Cabinet • Opensource (C, LGPL) • Successor to GDBM and QDBM • Very efficient in both space and speed • Simple key/value pairs • Multiple storage strategies • Multiple client language interfaces • Local storage only: no network interface • But see Tokyo Tyrant
  • 206.
  • 207.
    Cassandra • Open source(Java, Apache 2)
  • 208.
    Cassandra • Open source(Java, Apache 2) • Originally developed at Facebook
  • 209.
    Cassandra • Open source(Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage
  • 210.
    Cassandra • Open source(Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication
  • 211.
    Cassandra • Open source(Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication • Used by Facebook, Digg, Twitter, Rackspace
  • 212.
    Cassandra • Open source(Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication • Used by Facebook, Digg, Twitter, Rackspace • Eventually consistent
  • 213.
    Cassandra • Open source(Java, Apache 2) • Originally developed at Facebook • Uses key-column-value storage • High availability/elastic through replication • Used by Facebook, Digg, Twitter, Rackspace • Eventually consistent • Queries can ask “majority” or “all”
  • 214.
  • 215.
  • 216.
    GT.M • Open Source(Mumps, GPL) • Commercial support from Fidelity
  • 217.
    GT.M • Open Source(Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs
  • 218.
    GT.M • Open Source(Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs • Transactions via optimistic concurrency
  • 219.
    GT.M • Open Source(Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs • Transactions via optimistic concurrency • Everything you read must be unchanged
  • 220.
    GT.M • Open Source(Mumps, GPL) • Commercial support from Fidelity • Distributed persistence of key/value pairs • Transactions via optimistic concurrency • Everything you read must be unchanged • Mumps-to-C-to-Mumps APIs
  • 221.
  • 222.
  • 223.
  • 224.
  • 225.
  • 226.
    Mnesia • Open source(Erlang, Erlang license)
  • 227.
    Mnesia • Open source(Erlang, Erlang license) • Key/value pairs
  • 228.
    Mnesia • Open source(Erlang, Erlang license) • Key/value pairs • Value is any Erlang datatype
  • 229.
    Mnesia • Open source(Erlang, Erlang license) • Key/value pairs • Value is any Erlang datatype • Live reconfiguration
  • 230.
    Mnesia • Open source(Erlang, Erlang license) • Key/value pairs • Value is any Erlang datatype • Live reconfiguration • Supports transactions and distribution
  • 231.
  • 232.
    Hbase • Open source(Java, Apache 2)
  • 233.
    Hbase • Open source(Java, Apache 2) • Mimics Google’s “BigTable”
  • 234.
    Hbase • Open source(Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards
  • 235.
    Hbase • Open source(Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards • Runs on Hadoop Distributed File System
  • 236.
    Hbase • Open source(Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards • Runs on Hadoop Distributed File System • Java, REST, Thrift APIs
  • 237.
    Hbase • Open source(Java, Apache 2) • Mimics Google’s “BigTable” • Push map/reduce down to shards • Runs on Hadoop Distributed File System • Java, REST, Thrift APIs • Might be the DB behind Bing
  • 238.
  • 239.
  • 240.
    Hypertable • Open source(C++, GPL 2) • Yet another BigTable clone
  • 241.
    Hypertable • Open source(C++, GPL 2) • Yet another BigTable clone • Designed for highly scalable data storage
  • 242.
  • 243.
  • 244.
    Object database • Db4o •InterSystems Cache
  • 245.
    Object database • Db4o •InterSystems Cache • ZODB
  • 246.
    Object database • Db4o •InterSystems Cache • ZODB • GemStone/S
  • 247.
    Object database • Db4o •InterSystems Cache • ZODB • GemStone/S • Magma
  • 248.
  • 249.
    Db4o • Open source(Java/C#, GPL)
  • 250.
    Db4o • Open source(Java/C#, GPL) • Commercial license/support available
  • 251.
    Db4o • Open source(Java/C#, GPL) • Commercial license/support available • Supports object persistence
  • 252.
    Db4o • Open source(Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net
  • 253.
    Db4o • Open source(Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS
  • 254.
    Db4o • Open source(Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS • Supports class migration
  • 255.
    Db4o • Open source(Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS • Supports class migration • ... if you provide the code
  • 256.
    Db4o • Open source(Java/C#, GPL) • Commercial license/support available • Supports object persistence • both Java and dot-net • Can replicate to traditional RDBMS • Supports class migration • ... if you provide the code • Large community
  • 257.
  • 258.
  • 259.
    InterSystems Cache • Commercial •“World’s fastest object database”
  • 260.
    InterSystems Cache • Commercial •“World’s fastest object database” • Cross-platform
  • 261.
    InterSystems Cache • Commercial •“World’s fastest object database” • Cross-platform • Persistence of multidimensional arrays
  • 262.
    InterSystems Cache • Commercial •“World’s fastest object database” • Cross-platform • Persistence of multidimensional arrays • Similar to MUMPS/Pick data
  • 263.
    InterSystems Cache • Commercial •“World’s fastest object database” • Cross-platform • Persistence of multidimensional arrays • Similar to MUMPS/Pick data • Can be embedded in web pages
  • 264.
  • 265.
    ZODB • Open source(Python, Zope license)
  • 266.
    ZODB • Open source(Python, Zope license) • “Seamless object persistence”
  • 267.
    ZODB • Open source(Python, Zope license) • “Seamless object persistence” • Transactions, MVCC
  • 268.
    ZODB • Open source(Python, Zope license) • “Seamless object persistence” • Transactions, MVCC • Scaling across a network
  • 269.
    ZODB • Open source(Python, Zope license) • “Seamless object persistence” • Transactions, MVCC • Scaling across a network • Widely used
  • 270.
    ZODB • Open source(Python, Zope license) • “Seamless object persistence” • Transactions, MVCC • Scaling across a network • Widely used • Zope Replication Services (commercial)
  • 271.
  • 272.
    GemStone/S • Commercial (freelicense for small apps)
  • 273.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist”
  • 274.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist” • Includes Java interface
  • 275.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades
  • 276.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable
  • 277.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic
  • 278.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic • JPM’s Kapital created the financial crisis :)
  • 279.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic • JPM’s Kapital created the financial crisis :) • Integrates with Seaside
  • 280.
    GemStone/S • Commercial (freelicense for small apps) • Smalltalk objects just “persist” • Includes Java interface • Automatic and/or guided class upgrades • Horizontally scaleable • OOCL manages 40% of overseas traffic • JPM’s Kapital created the financial crisis :) • Integrates with Seaside • Web apps with transparent persistence
  • 281.
  • 282.
    Magma • Open source(Squeak Smalltalk, MIT)
  • 283.
    Magma • Open source(Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence
  • 284.
    Magma • Open source(Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S”
  • 285.
    Magma • Open source(Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model
  • 286.
    Magma • Open source(Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model • HA mode (multiple slaves ready for master)
  • 287.
    Magma • Open source(Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model • HA mode (multiple slaves ready for master) • Transaction-based (commit/rollback)
  • 288.
    Magma • Open source(Squeak Smalltalk, MIT) • Transparent Smalltalk object persistence • “Free GemStone/S” • Client-server model • HA mode (multiple slaves ready for master) • Transaction-based (commit/rollback) • Works nicely with Seaside
  • 289.
  • 290.
    In summary • Lotsof ways to not use SQL
  • 291.
    In summary • Lotsof ways to not use SQL • Many open source
  • 292.
    In summary • Lotsof ways to not use SQL • Many open source • Many commercially supported
  • 293.
    In summary • Lotsof ways to not use SQL • Many open source • Many commercially supported • Don’t assume you need an ORM!
  • 294.
  • 295.
    How to contactme • Email: merlyn@stonehenge.com
  • 296.
    How to contactme • Email: merlyn@stonehenge.com • Twitter: @merlyn
  • 297.
    How to contactme • Email: merlyn@stonehenge.com • Twitter: @merlyn • Website: www.stonehenge.com
  • 298.
    How to contactme • Email: merlyn@stonehenge.com • Twitter: @merlyn • Website: www.stonehenge.com • Phone: +1 503 777 0095