The Stinger Initiative: Making Apache Hive 100 Times Faster by Alan Gates.
From the post:
Introduced by Facebook in 2007, Apache Hive and its HiveQL interface has become the de facto SQL interface for Hadoop. Today, companies of all types and sizes use Hive to access Hadoop data in a familiar way and to extend value to their organization or customers either directly or though a broad ecosystem of existing BI tools that rely on this key proven interface. The who’s who of business analytics have already adopted Hive.
Hive was originally built for large-scale operational batch processing and it is very effective with reporting, data mining and data preparation use cases. These usage patterns remain very important but with widespread adoption of Hadoop, the enterprise requirement for Hadoop to become more real time or interactive has increased in importance as well. At Hortonworks, we believe in the power of the open source community to innovate faster than any proprietary offering and the Stinger initiative is proof of this once again as we collaborate with others to improve Hive performance.
So, What is Stinger?
Enabling Hive to answer human-time use cases (i.e. queries in the 5-30 second range) such as big data exploration, visualization, and parameterized reports without needing to resort to yet another tool to install, maintain and learn can deliver a lot of value to the large community of users with existing Hive skills and investments.
To this end, we have launched the Stinger Initiative, with input and participation from the broader community, to enhance Hive with more SQL and better performance for these human-time use cases. All the while, HiveQL remains the same before and after these advancements so it just gets better. And in keeping with the ecosystem of existing tools, it is complementary to best-of-breed data warehouses and analytic platforms.
Leveraging on existing skills and infrastructure.
Who knows? Hortonworks maybe about to start a trend!