What is Mara?
A lightweight ETL framework with a focus on transparency and complexity reduction.
Mara is a tool in the Big Data Tools category of a tech stack.
Mara is an open source tool with GitHub stars and GitHub forks. Here’s a link to Mara's open source repository on GitHub
Who uses Mara?
Pros of Mara
Great developing experience
UI focused on ETL development
- 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.
Mara Alternatives & Comparisons
What are some alternatives to Mara?
See all alternatives
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Riot brings custom tags to all browsers. Think React + Polymer but with enjoyable syntax and a small learning curve.
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.
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
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.