NoSQL Simplified: Schema vs. Schema-less

The Database for Big Data
Solutions

NoSQL Simplified:
Schema vs Schema-less
Leon Guzenda & Nick Quinn
Meetup - February 20, 2014
© Objectivity, Inc. 2014

!1

Overview
• Objectivity Inc. 
• Pros & Cons: 
• Schema
• Schema-less 
• What We Provide 
• A Compromise

!2

Objectivity, Inc.
• Headquartered in San Jose, CA
• Over two decades of NoSQL and Big Data experience
• Enables complex data virtualization and Big Data
solutions for the enterprise
• Software products:
• Objectivity/DB
• InfiniteGraph
• InfiniteGraph Social App
• Embedded in hundreds of enterprises, government
organizations and products, with millions of
deployments.

!3

Objectivity/DB
• Fully distributed object database. 
• Handles complex, highly inter-related data. 
"
• Extremely fast navigational access. 
• Scalable collections and B-Tree indices 
• ACID transactions plus Multi-Reader, One Writer mode. 
• Highly scalable - Single Logical View plus simple servers 
• Parallel Query Engine and Relationship Analytics 
• Fully interoperable C++, C#, Java, Python and SQL++ on
Windows, Unix, Linux and Mac OS X.

!4

ODBMS Deployments

Data Fusion

Big Science

Monitoring & Response

Telecom Infrastructure

Complex Financial Systems
!5

InfiniteGraph
• Fully distributed graph database 
• High throughput and scalability 
"
• Extremely fast navigational access 
• ACID transactions for online operation 
• Relaxed consistency during batch-mode parallel ingest 
• Parallel queries 
• Flexible indexing, including Lucene for text 
• Java API and Gremlin support

!6

Graph DBMS - Finding The Links

OTHER
DATABASE(S)

GRAPH DATABASE


!7

Objectivity’s Disruptive Big Data Architecture
Uses Data Virtualization to hide the nodes and focus on the connections


!8

Schema: Pros & Cons


!9

Who's Who?
• SCHEMA:
• Network [CODASYL] databases - DDL [1972]
• Relational Databases - Data Dictionary
• Object Databases - ODMG'93
• Most Graph Databases
"
• Schema-less:
• KSAM/ISAM/DSAM/ESAM
• IMS (hierarchical)
• Pick OS Database (hash-tables)
• MUMPS (hierarchical array-storage)
• MongoDB - a specialized JSON (and JSON-like)
document store.
• CouchDB - a JSON document store.

!10

Schema: Pros...
• Global data definitions
"
• Optimal access
"
• Enables Query By Example
"
• Interoperability
"
• Schema change control
"
• Schema contents can be manipulated via standard
APIs and tools

!11

...Schema: Pros
• Global data definitions:
• Data types and the relationships between them
• Makes queries more efficient
• Actions can be restricted by data type, field values, relationship types

"

• Optimal access:
• Used to determine how to best store, manage and access particular data types

"

• Enables Query By Example by showing:
• Types of information available
• Relationships between them

"

• Interoperability:
• DBMS can change the shape of data items to suit the language/environment

"

• Schema change control:
• Can be used to enforce workflows that will keep applications and data in sync.

"

• Schema contents can be manipulated via standard APIs and tools:
• Easier learning curve
• Uniform security controls:
• The schema can use the same security controls as the data
• Query and visualization tools can be used for both data and schema

!12

Schema: Cons
• The database designer and application developers have
to create and maintain the schema.
"
• Applications have to be kept in sync with schema
changes.
"
• Applications and programmers have to be aware of data
types
• Though this is one of the major claimed advantages of objectoriented programming.

"
• There is a perceived loss of flexibility

• Though this is more a function of the user interface to the
database than the underlying mechanisms.


!13

Schema-less: Pros…
• Flexibility
"
• Can be more tolerant of variable Acidity and
Consistency models
"
• Ease of use and maintenance:


!14

…Schema-less: Pros
• Flexibility - Users can, in theory:

"

• Put any kind of data into the system
• Create new kinds of relationships between things (in a few
products)
• Find data without worrying about the types of data
involved.

"

• Can be more tolerant of variable Acidity and Consistency
models

"

• Ease of use and maintenance:
• No need to worry about data types
• No need for a DBA
• Applications will [probably] work when new data arrives

!15

Schema-less: Cons…
• Confusion
"
• Performance suffers
"
• poor Integrity
"
• Ambiguity


!16

…Schema-less: Cons
• Apparent tolerance of variable CAP models is actually orthogonal to
the schema vs schema-less debate [as is support for sharding].

"


"

• Integrity is practically non-existent
• Maintaining referential integrity is hard
• Queries may misinterpret values within an object
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616e6f7468657220737472696e67


!17

Schema-less: Cons

"


"

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616e6f7468657220737472696e67 
 
 
Floating Point
 


!18

Schema-less: Cons

"


"

• 54686973206973206120737472696e6720706c7573206120666c6f
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616e6f7468657220737472696e67 
 
 
Floating Point
 
• A ZIPcode may be stored as an integer (01234) or a string (“01234”)
in JSON, causing query and display problems.

!19

The NoSQL Players
Operational

*

Intersystems

MarkLogic

McObject

Object/Graph
Objectivity/DB
Progress
Versant

"

Key-Value

*

Document

Berkeley DB
Cassandra
Redis
Riak
Voldemort

AppEngine
Cloudant
CouchDB
MongoDB
RavenDB

Couchbase


*

AllegroGraph
InfiniteGraph
Neo4j
Titan
Column Family
HBase
HyperTable
SimpleDB

* Fully or partially schema-less

!20

A Compromise 
Provide Flexibility With The Advantages Of Having A Schema


!21

Objectivity/DB Schema Usage
• Has an internal schema in its system database (the Federated DB).

"

• User schemas are created and updated by:
• Creating .ddl files and pre-processing them with the DDL processor.
• Creating and compiling Java, C# or Python header files.
• Declaring or dynamically creating/modifyingSmalltalk classes (defunct).
• Declaring and changing table definitions with Objectivity/SQL++.

"

• SQL++ table/column definitions are updated automatically when classes are
declared or modified using other languages.
• This allows SQL++ to access C#, C++, Java and Python objects and vice-versa.

"

• A Federated Database can contain multiple named Schemas:
• Reduces re-compilation and re-building after a localized schema change.
• May facilitate security mechanisms in the future.


!22

Objectivity Active Schema
"

• API and tools for creating, modifying, reading and deleting class
definitions, which include association (relationship) definitions.
• If used with a dynamic language, such as Smalltalk, creating or
modifying a class doesn't need to affect existing programs.
• In general, only generic access (via the ooObj base clase) can be used
without creating the files needed to recompile programs and methods
for accessing the new object types.

"

• Helps application developers build tools that need to access the schema,
e.g.:
• Graphical query tools
• highly flexible object modeling capabilities for end users.

"

• An end-user, such as a field technician or an analyst:
• Can add local object classes, populate, maintain and query them,
but...
• Cannot interfere with the correct operation of the pre-built
applications.

!23

Use Cases


!24

Use Case 1 - Intelligence Gathering Framework…
1

of

• An integrated application
development framework that
focuses on adaptability. 
• Dynamic modeling of
entities, services and
workflows.  
• Versioning and temporality
features support system
evolution. 
The screenshots show a location that is under surveillance and
everything known about it in the database.


!25

2

…Use Case 1 - Intelligence Gathering Framework
2

• Eliminates the mapping layer
between the user defined
objects and the database. 
• Performance and scalability.  

Design and Information Feeds

of

Users

Database

• Active Schema facilitates
object migration. 


!26

2

Use Case 2 - GDMO Framework
"
• Operations, Administration, and"
Maintenance interface for the CDMA"
system RF infrastructure 
• Controls the Base Station Controller and
Base Station Transceiver Subsystem 
• GDMO* Schema and CMIP agent-manager"
messaging 
• A SPARC-based BSC rack supports a"
peak load of 150,000 simultaneous callers 
• Deployed in CDMA networks worldwide,"
including SprintPCS"

* GDMO is the Guideline for the Definition of Managed Objects

!27

Use Case 3 - Ontology Framework
SCHEMA

"
• Uses standard objects to define a metaschema  
• It is used to define concept templates 
• They can be inherited from, combined or
extended to support a “class specification” 

CONCEPT

LOGIC

CLASS

COMPONENTS

• The data is combined with Horn Logic to
build complex ontologies."
RELATIONSHIP

STRUCT

ARRAY

FIELD

* GDMO is the Guideline for the Definition of Managed Objects

!28

Summary
• Don’t confuse CAP issues with Schema
considerations 
• Schemas make the DBMS more powerful 
• Schema-less architectures are more flexible 
• It’s possible to build flexible systems with
Schema-based infrastructure


!29

THANK YOU
• Please visit objectivity.com for: 
•
•
•
•
•
•

Features
Use Cases
White Papers
Free downloads (60 day evaluation)
Sample Applications
Application Developer’s Wiki

"

• For further information:

"

• Email: info@objectivity.com


!30

NoSQL Simplified: Schema vs. Schema-less

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