CDAP vs Apache Impala

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CDAP

19
74
+ 1
0
Apache Impala

116
243
+ 1
18
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CDAP vs Impala: What are the differences?

Developers describe CDAP as "Open source virtualization platform for Hadoop data and apps". 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. On the other hand, Impala is detailed as "Real-time Query for Hadoop". 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.

CDAP and Impala can be categorized as "Big Data" tools.

Some of the features offered by CDAP are:

  • Streams for data ingestion
  • Reusable libraries for common Big Data access patterns
  • Data available to multiple applications and different paradigms

On the other hand, Impala provides the following key features:

  • Do BI-style Queries on Hadoop
  • Unify Your Infrastructure
  • Implement Quickly

CDAP and Impala are both open source tools. Impala with 2.18K GitHub stars and 824 forks on GitHub appears to be more popular than CDAP with 346 GitHub stars and 178 GitHub forks.

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Pros of CDAP
Pros of Apache Impala
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    • 11
      Super fast
    • 1
      Repkication
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      Massively Parallel Processing
    • 1
      Scalability
    • 1
      Distributed
    • 1
      High Performance
    • 1
      Load Balancing
    • 1
      Open Sourse

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    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.

    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.

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    What companies use CDAP?
    What companies use Apache Impala?
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    What tools integrate with CDAP?
    What tools integrate with Apache Impala?

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    What are some alternatives to CDAP and Apache Impala?
    Airflow
    Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
    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.
    Akutan
    A distributed knowledge graph store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world.
    Apache NiFi
    An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
    StreamSets
    An end-to-end data integration platform to build, run, monitor and manage smart data pipelines to deliver continuous data for DataOps
    See all alternatives