Impala Now A Top-Level Project

Kevin Feasel

2017-12-06

Hadoop

Greg Rahn announces that Apache Impala is now a top-level project:

Five years ago, Cloudera shared with the world our plan to transfer the lessons from decades of relational database research to the Apache Hadoop platform via a new SQL engine — Apache Impala — the first and fastest open source MPP SQL engine for Hadoop.  Impala enabled SQL users to operate on vast amounts of data in open formats, stored on HDFS originally (with Apache Kudu, Amazon S3, and Microsoft ADLS now also native storage options), and do so in an interactive and iterative manner, which was previously not possible.  Its flexibility and leading analytic database performance drove the strong adoption of Impala across a wide range of global enterprises looking to power these BI and SQL analytic workloads, and led to a constantly growing ecosystem of third-party tools integrating with Impala.

Fast forward three years, Cloudera donated Impala to the Apache Software Foundation, along with the newly announced Apache Kudu project, further solidifying its place in the open source SQL world.  Since the proposal, the Impala engineering team has worked hard to bring Impala to the new software governance model of the Apache Incubator and build an active and innovative community. That’s why we are pleased to announce that Impala has graduated to a Top-Level Apache Software Foundation Project.

Congratulations go out to Cloudera and everyone who has worked on Imapala over the years.

Related Posts

Security Improvements In Kafka And Confluent Platform

Vahid Fereydouny demonstrates a number of security improvements made to Apache Kafka 2.0 as well as Confluent Platform 5.0: Over the past several quarters, we have made major security enhancements to Confluent Platform, which have helped many of you safeguard your business-critical applications. With the latest release, we increased the robustness of our security feature […]

Read More

SparkSession Versus SparkContext

Abhishek Baranwal explains the differences between the SparkSession object and the SparkContext object when writing Spark code: Prior to spark 2.0, SparkContext was used as a channel to access all spark functionality. The spark driver program uses sparkContext to connect to the cluster through resource manager. SparkConf is required to create the spark context object, […]

Read More

Categories

December 2017
MTWTFSS
« Nov Jan »
 123
45678910
11121314151617
18192021222324
25262728293031