+ 1

What is Apache Impala?

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
Apache Impala is a tool in the Big Data Tools category of a tech stack.
Apache Impala is an open source tool with 30 GitHub stars and 32 GitHub forks. Here’s a link to Apache Impala's open source repository on GitHub

Who uses Apache Impala?

20 companies reportedly use Apache Impala in their tech stacks, including Stripe, Agoda, and Expedia.com.

122 developers on StackShare have stated that they use Apache Impala.

Apache Impala Integrations

Hadoop, Redash, Mode, Apache Kudu, and Apache Parquet are some of the popular tools that integrate with Apache Impala. Here's a list of all 7 tools that integrate with Apache Impala.
Pros of Apache Impala
Super fast
Massively Parallel Processing
Load Balancing
High Performance
Open Sourse
Decisions about Apache Impala

Here are some stack decisions, common use cases and reviews by companies and developers who chose Apache Impala in their tech stack.

I have been working on a Java application to demonstrate the latency for the select/insert/update operations on KUDU storage using Apache Kudu API - Java based client. I have a few queries about using Apache Kudu API

  1. Do we have JDBC wrapper to use Apache Kudu API for getting connection to Kudu masters with connection pool mechanism and all DB operations?

  2. Does Apache KuduAPI supports order by, group by, and aggregate functions? if yes, how to implement these functions using Kudu APIs.

  3. How can we add kudu predicates to Kudu update operation? if yes, how?

  4. Does Apache Kudu API supports batch insertion (execute the Kudu Insert for multiple rows at one go instead of row by row)? (like Kudusession.apply(List);)

  5. Does Apache Kudu API support join on tables?

  6. which tool is preferred over others (Apache Impala /Kudu API) for read and update/insert DB operations?

See more

Apache Impala's Features

  • Do BI-style Queries on Hadoop
  • Unify Your Infrastructure
  • Implement Quickly
  • Count on Enterprise-class Security
  • Retain Freedom from Lock-in
  • Expand the Hadoop User-verse

Apache Impala Alternatives & Comparisons

What are some alternatives to Apache Impala?
Distributed SQL Query Engine for Big Data
Apache Drill
Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel.
Apache Hive
Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
See all alternatives

Apache Impala's Followers
301 developers follow Apache Impala to keep up with related blogs and decisions.