Evolution in technology, social media, and digital business has resulted in an explosion of data that can be mined by organizations to improve their business. The digital universe is growing: more than half of the data generated today is unstructured data from social networks, mobile/smart devices, web applications, and the like.

Unfortunately, traditional RDBMSs were designed for structured data. Although these databases have been the foundation for data management technology for more than three decades, the way applications are built has changed to the point where having one can restrict business agility, limit scalability, and strain budgets.

As a result, NoSQL databases, which are designed for web applications, metadata storage, and social media analytics, have gained traction over the last few years. Let’s take a look at how NoSQL databases like MongoDB compare with an RDBMS.

Today’s digital businesses demand:

• Fast, agile development
• Flexible data architecture (often called schema-less DB design)
• Scalability for big data
• Real-time performance (consistent UX across all interfaces)
• The ability to handle complex data types (text, media files, etc.)
• The ability to handle new computing environments (e.g., cloud)

Because traditional RDBMS were hard to scale, IT experts turned to RAC and clusters. But that did not solve the problem. The main problem is that SQL operations and transactions spanning multiple nodes do not scale well. In contrast, an open source, document-oriented database like MongoDB handles such requirements efficiently. MongoDB provides:

• A document data model (data is stored in a structure that maps to objects in modern programming language)
• Rich queries (indexes, queries, aggregation framework, native MapReduce, text search indexes)
• Drivers (applications interact with database using native libraries)
• Horizontal scalability (commodity hardware and cloud infrastructure are used to handle growth in data volume and throughput)
• High availability (support for native replication, automatic failover to secondary nodes)
• In-memory performance (e.g., data is read and written to RAM)
• Flexibility (flexible architecture supports changes to data models)

Database performance is the most important factor in successful application development. Unlike a traditional RDBMS, which demands a high level of performance-engineering knowledge, NoSQL databases like MongoDB make extensive use of RAM to optimize database performance. (Reading data from memory is faster than reading data from the disk.) MongoDB uses memory mapped files to optimize read operations. If the volume of data that is frequently accessed exceeds the capacity of single machine, MongoDB scales horizontally across multiple servers through automatic sharding. That is the key factor.

Post Date: 18-03-2016