I am sure most of you heard about market buzz words nosql,newsql... and it often make our DW developers to get confused on this new terms.Most of us just read about these new terms in the web without understanding it.
During my seminar users often question me why should I move into this new technology when the current DBMS has been around for 25+ years and how this is going to change the world.
Before I get into a discussion , lets just start from the basic..
What is NOSQL ?
NOSQL holds a wide variety of different database technologies developed using(JSON,python..) to address volume of data we generate today(like facebook,twitter,..), handling unstructured data,agile methodology,scalable processing needs.
NOSQL Database Types
Document databases pair each key with a complex data structure known as a document. Documents can contain many different key-value pairs, or key-array pairs, or even nested documents.
Graph stores are used to store information about networks, such as social connections. Graph stores include Neo4J and HyperGraphDB.
Key-value stores are the simplest NoSQL databases. Every single item in the database is stored as an attribute name (or "key"), together with its value. Examples of key-value stores are Riak and Voldemort. Some key-value stores, such as Redis, allow each value to have a type, such as "integer", which adds functionality.
Wide-column stores such as Cassandra and HBase are optimized for queries over large datasets, and store columns of data together, instead of rows.
When Should I go for Nosql ?
I would say it's depends on the nature of data, if you have simple table structure, spreadsheet, delimited text or others files then you can follow the current RDBMS database which requires you to define the schema before processing it.
Data such us geo-spatial,modecular modeling or very complex and unstructured data then go for Nosql.I am sure you would of spent hours and hours on modeling them into relational tables in past, NOSQL databases allows you to store them without defining schema and allows you make any changes without changing the existing model.
Relational databases require you to define schemas before you can add data. For example, you might want to store data about your customers such as phone numbers, first and last name, address, city and state – a SQL database needs to know what you are storing in advance.
NoSQL databases are built to allow the insertion of data without a predefined schema. That makes it easy to make significant application changes in real-time, without worrying about service interruptions – which means development is faster, code integration is more reliable, and less database administrator time is needed.
Data warehousing & BI analytics
RDBMSes are ideally suited for complex query and analysis. Even in today’s world, Hadoop data is sometimes loaded back to an RDBMS for reporting purposes. So an RDBMS is a good choice if the query and reporting needs are very critical.
Real time analytics for operational data is better suited to a NoSQL setting. Further, in cases where data is brought together from many upstream systems to build an application (not just reporting), NoSQL is a must. Today, BI tool-support for NoSQL is new, but growing rapidly.
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