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CDAP
CDAP

5
9
+ 1
0
EventQL
EventQL

3
6
+ 1
3
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CDAP vs EventQL: 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, EventQL is detailed as "The database for large-scale event analytics". EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries.

CDAP and EventQL belong to "Big Data Tools" category of the tech stack.

CDAP and EventQL are both open source tools. EventQL with 1.02K GitHub stars and 91 forks on GitHub appears to be more popular than CDAP with 346 GitHub stars and 178 GitHub forks.

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 EventQL?

EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries.
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            What are some alternatives to CDAP and EventQL?
            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.
            Amazon Athena
            Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
            Apache Flink
            Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
            Presto
            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 Hive
            Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
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