Just a few years after the concept of structured query tools was first introduced, there are already dozens of vendors offering SQL capabilities for the batch processing platform, from small-time players such as Hadapt and Splice Machine to industry bigwigs like Cloudera. But despite the tremendous market saturation, the latest company to hop on the bandwagon has succeeded in raising eyebrows.

Oracle on Tuesday pulled the curtains back on a new software feature meant to make it possible for users to access and manipulate their fast-growing troves of unstructured data without having to learn the nuances of the individual systems in which that information is stored. The capability allows organizations to harness the existing SQL proficiency of practitioners and business analysts instead of having to hire expensive specialized talent, a benefit that can add up to a great deal of cost and time savings at large scale.

Hadoop is only one of the technologies supported in Oracle Big Data SQL. The tool also works with the company’s flagship relational system and, in a gesture of interoperability entirely uncharacteristic of Larry Ellison’s firm,  competing non-relational systems as well. But, upon closer inspection, the decision to provide support for that fast-growing category of databases reveals itself to be merely the newest example of a legacy vendor embracing an “if you can’t beat ‘em, support ‘em” mentality towards a trend they had tried but ultimately failed ignoring into non-existence.

In terms of functionality, the offering sets itself apart by leveraging the Smart Scan technology from Oracle’s Exadata line of database appliances, which offloads common query operations to the storage layer in order to reduce the amount of information that has to travel through the network back to the server.  That allows users to get to their data much faster and easier than would be possible using regular connectors.

Another major advantage of Big Data SQL is that it eliminates the need  to write the same request multiple times in the all the different native formats of the systems to be queried. That task not only takes up time better spent elsewhere, bottlenecking the entire data processing pipeline in the process, but also opens the door to inconsistencies that can be tremendously difficult to track down and have the potential to wreak havoc further down the analytics lifecycle.  Oracle’s approach solves that with one fell swoop.

The value proposition is solid, but it’s practically identical to what Teradata is offering with QueryGrid, a complementary tool for its flagship data warehousing platform that was introduced in April with the promise of enabling  the exact same combination of simplicity and faster response times. Yet although it’s somewhat late to the party, Oracle has the advantage of having a largest customer base and channel footprint, which places Big Data SQL on a much more aggressive trajectory than QueryGrid. Whether the database giant will be able to sustain that trajectory still remains to be seen, however.

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