Companies have come to depend on open source products like Apache Drill to meet their data storage and analysis needs. As data architectures become more distributed, it can be difficult to access data from a single application. Progress DataDirect offers a simple solution to this very complex business demand.
As businesses rely more and more on open source, cloud-based and SaaS applications, it has become increasingly important for them to be able to quickly access, manage and analyze their data in a succinct, all-inclusive manner. There are many proprietary and open-source tools on the market that can handle the workload of big data exploration, but they can’t always connect with the array of disparate data sources. Progress DataDirect can now help your business make these connections. But first, a little background info…
Apache Drill with RDBMS Storage Plugin
Apache Drill is one of the more popular open-source tools in use for querying non-relational datastores. An open source version of Google Dremel, Apache Drill allows users to simultaneously query and analyze a variety of NoSQL data sources in both cloud and on-premises locations. Additionally, with the RDBMS Storage Plugin enabled, Apache Drill can also push down into traditional databases like SQL Server, Postgres…etc.
There are extraordinary benefits for organizations to achieve this level of insight across so many enterprise systems, but it isn’t always easy to reap those benefits. While Apache Drill+RDBMS Storage Plugin can work with these datastores, they can’t always readily access them. That’s where DataDirect can help.
Making the Connection
Although it is possible to build and maintain internal drivers and APIs to access your enterprise data, the cost and resources necessary for the project can be cost-prohibitive. Progress DataDirect has a passion for solving such problems by building stable, out-of-the-box connections across applications, platforms and architectures. With just a few clicks, DataDirect JDBC Drivers enable you to connect Apache Drill to your relational and non-relational data sources.