The document discusses NoSQL databases and their advantages compared to SQL databases. It defines NoSQL as any database that is not relational and describes the main categories of NoSQL databases - key-value stores, document databases, wide column stores like BigTable, and graph databases. It also covers common use cases for different NoSQL databases and examples of companies using NoSQL technologies like MongoDB, Cassandra, and HBase.
An Intro to NoSQL Databases -- NoSQL databases will not become the new dominators. Relational will still be popular, and used in the majority of situations. They, however, will no longer be the automatic choice. (source : http://martinfowler.com/)
An Intro to NoSQL Databases -- NoSQL databases will not become the new dominators. Relational will still be popular, and used in the majority of situations. They, however, will no longer be the automatic choice. (source : http://martinfowler.com/)
158ltd.com gives a rapid introduction to NoSQL databases: where they came from, the nature of the data models they use, and the different way you have to think about consistency.
SQL vs NoSQL, an experiment with MongoDBMarco Segato
A simple experiment with MongoDB compared to Oracle classic RDBMS database: what are NoSQL databases, when to use them, why to choose MongoDB and how we can play with it.
Can No-SQL technologies hold for the specific requirements that apply to the Telco domain?
This is the Slideshare Presentation by Ericsson Researcher Nicolas Seyvet to accompany his blog "NoSQL for Telco"
http://labs.ericsson.com/blog/nosql-for-telco
MongoDB is a popular NoSQL database. This presentation was delivered during a workshop.
First it talks about NoSQL databases, shift in their design paradigm, focuses a little more on document based NoSQL databases and tries drawing some parallel from SQL databases.
Second part, is for hands-on session of MongoDB using mongo shell. But the slides help very less.
At last it touches advance topics like data replication for disaster recovery and handling big data using map-reduce as well as Sharding.
NoSQL, as many of you may already know, is basically a database used to manage huge sets of unstructured data, where in the data is not stored in tabular relations like relational databases. Most of the currently existing Relational Databases have failed in solving some of the complex modern problems like:
• Continuously changing nature of data - structured, semi-structured, unstructured and polymorphic data.
• Applications now serve millions of users in different geo-locations, in different timezones and have to be up and running all the time, with data integrity maintained
• Applications are becoming more distributed with many moving towards cloud computing.
NoSQL plays a vital role in an enterprise application which needs to access and analyze a massive set of data that is being made available on multiple virtual servers (remote based) in the cloud infrastructure and mainly when the data set is not structured. Hence, the NoSQL database is designed to overcome the Performance, Scalability, Data Modelling and Distribution limitations that are seen in the Relational Databases.
Introduction to MongoDB and CRUD operationsAnand Kumar
Learn about MongoDB basics, its advantages, history.
Learn about the installation of MongoDB.
Learn Basics of create,insert,update,delete documents in MongoDB.
Learn basics of NoSQL.
158ltd.com gives a rapid introduction to NoSQL databases: where they came from, the nature of the data models they use, and the different way you have to think about consistency.
SQL vs NoSQL, an experiment with MongoDBMarco Segato
A simple experiment with MongoDB compared to Oracle classic RDBMS database: what are NoSQL databases, when to use them, why to choose MongoDB and how we can play with it.
Can No-SQL technologies hold for the specific requirements that apply to the Telco domain?
This is the Slideshare Presentation by Ericsson Researcher Nicolas Seyvet to accompany his blog "NoSQL for Telco"
http://labs.ericsson.com/blog/nosql-for-telco
MongoDB is a popular NoSQL database. This presentation was delivered during a workshop.
First it talks about NoSQL databases, shift in their design paradigm, focuses a little more on document based NoSQL databases and tries drawing some parallel from SQL databases.
Second part, is for hands-on session of MongoDB using mongo shell. But the slides help very less.
At last it touches advance topics like data replication for disaster recovery and handling big data using map-reduce as well as Sharding.
NoSQL, as many of you may already know, is basically a database used to manage huge sets of unstructured data, where in the data is not stored in tabular relations like relational databases. Most of the currently existing Relational Databases have failed in solving some of the complex modern problems like:
• Continuously changing nature of data - structured, semi-structured, unstructured and polymorphic data.
• Applications now serve millions of users in different geo-locations, in different timezones and have to be up and running all the time, with data integrity maintained
• Applications are becoming more distributed with many moving towards cloud computing.
NoSQL plays a vital role in an enterprise application which needs to access and analyze a massive set of data that is being made available on multiple virtual servers (remote based) in the cloud infrastructure and mainly when the data set is not structured. Hence, the NoSQL database is designed to overcome the Performance, Scalability, Data Modelling and Distribution limitations that are seen in the Relational Databases.
Introduction to MongoDB and CRUD operationsAnand Kumar
Learn about MongoDB basics, its advantages, history.
Learn about the installation of MongoDB.
Learn Basics of create,insert,update,delete documents in MongoDB.
Learn basics of NoSQL.
Relational databases vs Non-relational databasesJames Serra
There is a lot of confusion about the place and purpose of the many recent non-relational database solutions ("NoSQL databases") compared to the relational database solutions that have been around for so many years. In this presentation I will first clarify what exactly these database solutions are, compare them, and discuss the best use cases for each. I'll discuss topics involving OLTP, scaling, data warehousing, polyglot persistence, and the CAP theorem. We will even touch on a new type of database solution called NewSQL. If you are building a new solution it is important to understand all your options so you take the right path to success.
An overview of various database technologies and their underlying mechanisms over time.
Presentation delivered at Alliander internally to inspire the use of and forster the interest in new (NOSQL) technologies. 18 September 2012
When it comes time to select database software for your project, there are a bewildering number of choices. How do you know if your project is a good fit for a relational database, or whether one of the many NoSQL options is a better choice?
In this webinar you will learn when to use MongoDB and how to evaluate if MongoDB is a fit for your project. You will see how MongoDB's flexible document model is solving business problems in ways that were not previously possible, and how MongoDB's built-in features allow running at scale.
Topics covered include:
Performance and Scalability
MongoDB's Data Model
Popular MongoDB Use Cases
Customer Stories
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...Lucas Jellema
This presentation gives an brief overview of the history of relational databases, ACID and SQL and presents some of the key strentgths and potential weaknesses. It introduces the rise of NoSQL - why it arose, what is entails, when to use it. The presentation focuses on MongoDB as prime example of NoSQL document store and it shows how to interact with MongoDB from JavaScript (NodeJS) and Java.
Big Data is the reality of modern business: from big companies to small ones, everybody is trying to find their own benefit. Big Data technologies are not meant to replace traditional ones, but to be complementary to them. In this presentation you will hear what is Big Data and Data Lake and what are the most popular technologies used in Big Data world. We will also speak about Hadoop and Spark, and how they integrate with traditional systems and their benefits.
How to Survive as a Data Architect in a Polyglot Database WorldKaren Lopez
Karen Lopez talks to data architects and data moders how they can best deliver value on modern data drive projects beyond relational database technologies. She covers NoSQL Databases and Datastores, which data stories they best fit and which ones they don't. She ends with 10 tips for adding more value to ployschematic database solutions.
4. In the early 1980s, relational databases began to
be defined. One of the proponents of relational
database theory was Edgar F. Codd, who
published 13 rules that set out to define a
relational database. This was the beginning of
the formalized scientific groundwork done to lay
down specific rules for the existence of the
relational aspects of a database.
Sursa: http://www.ehow.com
5. Relevant rules
• Relational facilities
• Information is represented only in one way
• All data must be accessible
• All views that are theoretically updatable
must be updatable by the system
• Insert, Update, Delete for any retrieval sets
13. Any database that is not a Relational
Database!
Simple like this
What is NoSQL?
14. • Non-Relational Database
• But is to long
• Is not so cool
• This name would not caught on
A better name would be
15. • Non-Relational Database
• But is to long
• Is not so cool
• This name would not caught on
…so we are back to
NoSQL
A better name would be
16.
17.
18. • More and more connections between data
• Everything is linked to something more… and
more… and so on
• Hyperlinks
• Tags
• RSS
• RDF
• Attributes
• User content
Database trends – 1 Connections
19. • From a flat architecture
Database trends – 2 Architecture
DB
App
20. • From a flat architecture to a couple one
Database trends – 2 Architecture
DB
AppApp App
21. • From a flat architecture to a couple one and now
we have a decoupled one based on services
Database trends – 2 Architecture
DB
App
DB
App
DB
App
22. • From web 2.0 the structure of data are don’t
have so fixed structure (is more flexible)
• How many phone number a person could have
in 1970?
Database trends – 3 No fix structure
23. • From web 2.0 the structure of data are don’t
have so fixed structure (is more flexible)
• How many phone number a person could have
in 1970? And NOW …
Database trends – 3 No fix structure
24. • 2006 - 160
• 2008 – 390
• 2010 – 998
• 2012 – 2000+
• First column is in years
• Second column is in … ?
Database trends – 4 Data Size
30. • Design to handle massive load
• Can scale to massive amounts of data
• Based on Key-Value collections
• Dynamic ring partition
• Dynamic replication
• Ex.: Dynoite
Key-Value
32. • Like column oriented Relational Database,
but with a twist
• Tables similar to RDBMS, but handle semi-
structured
• Based on Google’s BigTable paper
• Data mode:
• Columns – columns family -> ACL
• Dataums keyed by - row, column, time, index
• Row-range – table -> distribution
• Ex.: Cassandra
Big Table
33.
34. • Similar with Key-Value pair but
• DB knows what the Value is
• Inspired by Lotus Notes
• Data model:
• Collections of Key-Value collections
• Documents are often versioned
• Ex.: MongoDB
Document Database
35.
36. • Focus in modeling the structure of data
• The interconnectivity
• Scales on the complexity of data
• Inspired by mathematical Graph Theory
• Data model:
• Property Graph -> Nodes
• Relationships/Edges between Nodes
• Key-Value pair on both
• Possible Edge Labels and/or Node/Edge Types
• Ex.: Neo4j
Graph Database
37.
38.
39. • Not part of NoSQL community
• Still a good solution for a lot of problems
• Focuses on matching OOP paradigm
• Easy to use
• Simple to integrate
• Neither gain nor loosing traction
Object Database
40.
41. • Easy to deploy
• No OS management
• Scaling
• Monitoring
• Publish from different source controls
• Support different technologies (PHP, node.js,
.NET)
• Low cost support – shared mode
• Reserved mode – dedicated instance
• Each site run in an isolated environment
Web Sites
44. • REST
• GQL (SQL Like)
• SPARQL
• Gremlin
• API’s
How to query it?
45. • Replication
• Write to many
• Master/Slave replication
• Master reelection
• Failover
• Either by another machine taking over
• Client knowing
Availability
46. • Most NoSQL sacrifice Consistency
• Some NoSQL don’t have Transactions
• Atom single operations
• Because of this some operations are
impossible to implement
Correctness
51. • Why
• Dynamic query
• Content is stored as documents
• Big database that need to be very fast
• Where
• Properties are stored like query and index
• Can be used for voting system, CMS or comment
storage
MongoDB
52. • Why
• When you make a lot of updates and insert
• Reading data is not the main scope of the database
(writes are faster than reads)
• Content is stored as column
• High availability
• Where
• Can be used with success for logging
• Financial industry or any place where we work with a
lot of data that is needed to be written
• Basket of an e-commerce application
Cassandra
53. • Why
• For data that don’t change very often (insert
and read and NOT update)
• We have a lot of predefined queries and we
need versioning support
• Where
• Is a great database for CMS and CRM.
CouchDB
54. • Why
• When you do data analyzing
• Where
• Works great in combination with Hadoop
HBase
55. • Why
• When we need high concurrency
• When the latency is very low and we want
the latency to be minimal
• Where
• Backend of a game or a system that offer
data in real time
Membase
56. • Why
• When we need to make a lot of updates
• When the database is not too big and can be
kept in memory
• Where
• Can be used when we have a real time
communication, for example a stock market
with prices
Redis