Collections · For engineers
Databases and Data Engineering
The storage, streaming, and processing systems most data platforms are assembled from.
Last reviewed Oct 2, 2026. Open in the explorer to search and filter within it.
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Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
The relational database most projects should start with.
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For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
In-memory data structures for caching, queues, and counters.
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DuckDB is an analytical in-process SQL database management system
An embedded analytical database; SQL over local files with no server.
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ClickHouse® is a real-time analytics database management system
A column-oriented database for analytical queries over very large tables.
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Apache Kafka - A distributed event streaming platform
The standard distributed log for event streaming.
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Apache Spark - A unified analytics engine for large-scale data processing
Distributed batch and stream processing.
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Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Scheduling and monitoring for data pipelines defined in Python.