Amazon Web Services launched DynamoDB, as an NoSQL database designed for Internet scale web applications. The announcement is interesting for a couple of reasons. First, AWS’s database services provide reasonably priced, highly-available database services delivered on fast storage architecture based on Solid State Drives (SSD).

At $1 per month for a gigabyte of SSD managed, durable and highly-available storage, AWS is clearly going for the jugular early on other managed NoSQL solutions. Moreover, AWS has the added advantage of offering multiple other services in tandem with DynamoDB that are attractive when compared to using multiple hosted services.

However, the bigger question is what is the business potential for this service? A simple Google search on “Managed NoSQL Databases” results in numerous hits about DynamoDB, but forces one to dig to find the competitors in this space.

NoSQL Databasse

NoSQL (Not only SQL) is a broad class of database management systems that differ from the classic model of the relational database management system (RDBMS) in some significant ways. These data stores may not require fixed table schemas, typically refers as structured storage.

The top five advantages of NoSQL databases is as follows.

 1)Elastic scaling:

SQL databases have relied on scale up — buying bigger servers as database load increases — rather than scale out — distributing the database across multiple hosts as load increases. However, as transaction rates and availability requirements increase, and as databases move into the cloud or onto virtualized environments, the economic advantages of scaling out on commodity hardware become irresistible.

RDBMS might not scale out easily on commodity clusters, but the new breed of NoSQL databases are designed to expand transparently to take advantage of new nodes, and they’re usually designed with low-cost commodity hardware in mind.

2)Big data:

Just as transaction rates have grown out of recognition over the last decade, the volumes of data that are being stored also have increased massively. O’Reilly has cleverly called this the “industrial revolution of data.” RDBMS capacity has been growing to match these increases, but as with transaction rates, the constraints of data volumes that can be practically managed by a single RDBMS are becoming intolerable for some enterprises. Today, the volumes of “big data” that can be handled by NoSQL systems, such as Hadoop, outstrip what can be handled by the biggest RDBMS.

3)Economics:

NoSQL databases typically use clusters of cheap commodity servers to manage the exploding data and transaction volumes, while RDBMS tends to rely on expensive proprietary servers and storage systems. The result is that the cost per gigabyte or transaction/second for NoSQL can be many times less than the cost for RDBMS, allowing you to store and process more data at a much lower price point.

4)Goodbye DBAs: 

NoSQL databases are generally designed from the ground up to require less management: automatic repair, data distribution, and simpler data models lead to lower administration and tuning requirements — in theory. In practice, it’s likely that rumors of the DBA’s death have been slightly exaggerated. Someone will always be accountable for the performance and availability of any mission-critical data store.

5)Flexible data models:

NoSQL databases have far more relaxed — or even nonexistent — data model restrictions. NoSQL Key Value stores and document databases allow the application to store virtually any structure it wants in a data element. Even the more rigidly defined BigTable-based NoSQL databases (Cassandra, HBase) typically allow new columns to be created without too much fuss.