Hive on MR3

The best way to run Apache Hive in production

What do we do?

We develop an execution engine MR3 for big data processing and maintain it main application - Hive on MR3. Our execution engine MR3 provides native support for both Hadoop and Kubernetes.

We provide a quick and ready solution to the following problems.

#1. You want to install Hive on Hadoop or upgrade from an old version of Hive.

Installing Hive on Hadoop or upgrading to a higher version of Hive is not a simple task. Hive on MR3 is very easy to install and requires no change to an existing installation of Hadoop (such as HDP and CDH).

#2. You want to run Hive directly on Kubernetes.

As the enterprise environment gravitates towards Kubernetes at an accelerating pace, the industry is looking for a solution that enables Hive to run directly on Kubernetes. For this problem, Hive on MR3 is a perfect solution ready for you.

#3. You want to run Hive without installing Kubernetes or Hadoop.

MR3 supports standalone mode which does not require a resource manager such as Hadoop and Kubernetes. By exploiting standalone mode, you can run Hive on MR3 virtually in any type of cluster.

Why is our solution better than alternatives?

#1. Hive on MR3 is stable with about 800 security and critical patches backported.

Anyone who manually builds Apache Hive 3 (such as version 3.1.3) soon discovers that it is not really ready for production use because many important patches have not been merged. We have backported about 800 important patches to Hive on MR3 and keep backporting more patches.

#2. Hive on MR3 achieves the speed of LLAP and beyond.

LLAP (Low-Latency Analytical Processing) is a major component of Hive which allows it to far outperform competing technologies. Enabling LLAP, however, is excruciatingly difficult because of its complex architecture. Hive on MR3 automatically achieves the speed of LLAP and beyond with no additional configuration.

#3. Hive on MR3 achieves a much higher throughput than Hive on Tez.

A common use case of Hive on Tez is to run ETL (Extract-Transform-Load) jobs. By virtue of its advanced resource sharing model, Hive on MR3 can deliver significant cost savings, especially if many ETL jobs are run concurrently.

#4. Hive on MR3 supports Java 17.

Unlike Apache Hive which still requires Java 8, Hive on MR3 can run with Java 17. By switching to Java 17, Hive on MR3 can reduce the running time by up to 30%.

#5. Hive on MR3 supports Remote Shuffle Service.

Remote Shuffle Service is being adopted by a growing number of technologies because of its numerous potentials. Hive on MR3 is also evolving fast to support Remote Shuffle Service. Currently Hive on MR3 supports Apache Celeborn as Remote Shuffle Service and can eliminate over 95% of local disk writes.

#6. No vendor lock-in.

Running Hive on MR3 means that there is no risk of vendor lock-in. Since Hive on MR3 runs with Hive Metastore, the user can switch back to Apache Hive or an alternative technology at any time.

Try and evaluate Hive on MR3!

You can customize Hive on MR3.

Hive on MR3 consists of three components: MR3, Tez for MR3, and Hive for MR3. Users can rebuild Hive on MR3 after backporting additional patches of their choice from Apache Tez and Apache Hive.

Hive on MR3 is more open than popular open source products.

Unlike typical open source products which often omit critical features in their community editions, we provide all the enterprise features available in MR3. Since it is also customizable by users, Hive on MR3 is in fact more open than popular open source products that do not release the source code for their enterprise editions.

Ready to get started?

If you are interested in our solution, you can try it yourself or request a demo. For any question about our solution and commercial licenses, please contact us.

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