We announced Oracle Big Data SQL on July 15. There’s lots of other information on it elsewhere. Here are some to start with.
Here I want to focus on how Oracle Big Data SQL addresses those three key problems in building a Big Data Management System: skills, integration, and security.
First, we have those two different angles on skills. SQL is the most popular language for data scientists and it’s even more popular among other types of analysts. So being able to use those skills to work with data in Hadoop and NoSQL databases is a big deal. And those Hadoop skills your organization doesn’t have? Oracle Big Data Appliance comes with Hadoop installed and optimized: as ESG say, it’s 21% cheaper and 30% faster than doing it yourself (assuming you have those skills in the first place).
Next it’s about integration. And here the use of standard Oracle SQL pays real dividends. All those applications you have that talk to Oracle Database, all those dashboards that fetch data from an Oracle Data Warehouse – just add some additional queries and you’ve got access to data in Hadoop and NoSQL.
And finally there’s security. We’ve done a lot with Oracle Big Data Appliance to make it secure, with authentication (Kerberos), authorization (Apache Sentry), auditing (via integration with Oracle Audit Vault and Database Firewall), and encryption (of data at rest and in motion). But Oracle Big Data SQL brings perhaps the biggest advance of them all. Because you use SQL to access all the data in Hadoop and NoSQL through Oracle Database, it means that all the security policies you are already employing with Oracle Database can be extended to these new sources. In addition to all the other things above, you get data redaction, privilege analysis, and strong controls that limit privileged user access to data.
If you want to use big data in your company then you simply have to build a Big Data Management System, seamlessly integrating Hadoop and NoSQL with your existing data warehouse. Oracle Big Data SQL is the best way to get that done.