Git vs Mara
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. | A lightweight ETL framework with a focus on transparency and complexity reduction. |
| - | Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code.; PostgreSQL as a data processing engine.; Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines.; GNU make semantics. Nodes depend on the completion of upstream nodes. No data dependencies or data flows.; No in-app data processing: command line tools as the main tool for interacting with databases and data.; Single machine pipeline execution based on Python's multiprocessing. No need for distributed task queues. Easy debugging and and output logging.; Cost based priority queues: nodes with higher cost (based on recorded run times) are run first. |
Statistics | |
GitHub Stars 57.1K | GitHub Stars - |
GitHub Forks 26.9K | GitHub Forks - |
Stacks 343.7K | Stacks 5 |
Followers 184.2K | Followers 21 |
Votes 6.6K | Votes 3 |
Pros & Cons | |
Pros
Cons
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What are some alternatives to Git, 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.
Mercurial
Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds.
Presto
Distributed SQL Query Engine for Big Data
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.
SVN (Subversion)
Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.
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.
lakeFS
It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
Apache Kylin
Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
