Five Ways Automation Speeds Up Big Data Deployments
At the MongoDB World 2015 conference this week, MongoDB outlined forthcoming additions to the open source document database that cover everything from connectors to business intelligence applications that enable MongoDB to respond to SQL read requests to the ability to join data sets.
Kelly Stirman, vice president of strategy for MongoDB, says, in sum, the additions planned for a MongoDB 3.2 release due out later this year are designed to make database administrators more comfortable with MongoDB in a classic enterprise IT setting. For example, the new release will also include tools to more granularly defined schemas and data patterns within MongoDB, while also making it easier to discover what data is already in an existing instance of MongoDB.
With MongoDB itself being download over 10,000 times a day, Stirman says the number and types of applications that are starting to show up on the database have increased considerably in the last year. The top two use cases for MongoDB, says Stirman, usually involve some form of content management and, more recently, Internet of Things (IoT) applications that require access to analytics on an IoT gateway.
In the near future, however, Stirman says MongoDB also expects to see increased usage of the database as a front end for mainframes that increasingly now need to find a more cost-effective way to be integrated with mobile applications. In much the same way that MongoDB is deployed in an IoT environment, the MongoDB database can be used to process transaction and analytics simultaneously, with the mainframe application then updated by MongoDB, much like any other batch application.
As this juncture, it’s pretty clear that as a NoSQL database, MongoDB is in a class by itself in terms of adoption. The challenge now is finding a way to make MongoDB a more natural extension of the enterprise that both developers and DBAs can both appreciate.
