This on-demand webinar discusses current data management challenges organizations are facing and why NoSQL is critical. It demonstrates use cases and best practices for NoSQL.
A non-relational database is any database that does not follow the relational model provided by traditional relational database management systems. This category of databases, also referred to as NoSQL databases, has seen steady adoption growth in recent years with the rise of Big Data applications.
Non-relational databases have grown in popularity because they were designed to overcome the limitations of relational databases in dealing with Big Data demands. Big Data refers to data that is growing and moving too fast, and is too diverse in structure for conventional technologies to handle.
While these NoSQL technologies vary greatly, these databases are typically more scalable and flexible than their relational counterparts. Non-relational databases have evolved from relational technology in these ways:
- Data models: Unlike relational models which require predefined schema, NoSQL databases offer flexible schema design that make it much easier to update the database to handle changing application requirements.
- Data structure: Non-relational databases are designed to handle unstructured data that doesn’t fit neatly into rows and columns. This matters as most of the data generated today is unstructured.
- Scaling: You can scale your system horizontally by taking advantage of cheap, commodity servers.
- Development model: NoSQL databases are typically open source which means you don’t have to pay any software licensing fees upfront.
Of the many non-relational options that exist, MongoDB stands at the top with over 10 million downloads and hundreds of thousands of deployments. Gartner recently named MongoDB as a leader in their Magic Quadrant report on operational databasement management systems, which covers relational and non-relational systems. And according to the latest DB-Engines rankings, MongoDB leads all NoSQL database products.