Apache Spark vs. Impala vs. CDAP

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Apache Spark

Impala

CDAP

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Description

What is 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.

What is 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.

What is CDAP?

Cask Data Application Platform (CDAP) is an open source application development platform for the Hadoop ecosystem that provides developers with data and application virtualization to accelerate application development, address a broader range of real-time and batch use cases, and deploy applications into production while satisfying enterprise requirements.

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Why do you like Apache Spark?

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Why do you like Impala?

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Why do you like CDAP?

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Pricing

Companies

221 Companies Using Apache Spark
12 Companies Using Impala
2 Companies Using CDAP

Integrations

Apache Spark Integrations
Impala Integrations
CDAP Integrations

What are some alternatives to Apache Spark, Impala, and CDAP?

  • Apache Flink - Fast and reliable large-scale data processing engine
  • Druid - Fast column-oriented distributed data store
  • Presto - Distributed SQL Query Engine for Big Data (by Facebook)
  • Amazon Athena - Query S3 Using SQL

See all alternatives to Apache Spark



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