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EventQL
EventQL

3
6
+ 1
3
Mara
Mara

2
6
+ 1
3
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EventQL vs Mara: What are the differences?

EventQL: 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; Mara: A lightweight ETL framework. A lightweight ETL framework with a focus on transparency and complexity reduction.

EventQL and Mara can be primarily classified as "Big Data" tools.

EventQL and Mara are both open source tools. It seems that Mara with 1.24K GitHub stars and 51 forks on GitHub has more adoption than EventQL with 1.02K GitHub stars and 91 GitHub forks.

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.

What is Mara?

A lightweight ETL framework with a focus on transparency and complexity reduction.
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              What are some alternatives to EventQL and Mara?
              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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