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 2.3K GitHub stars and 844 GitHub forks. Here’s a link to Apache Impala's open source repository on GitHub
Who uses Apache Impala?
18 companies reportedly use Apache Impala in their tech stacks, including Stripe, Agoda, and Expedia.com.
64 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 5 tools that integrate with Apache Impala.
Pros of Apache Impala
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?
See all alternatives
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
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.
Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
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.