Why openLooKeng?

Data Analysis Across Data Centers

Unified SQL interfaces ensure data access across data centers and hybrid clouds.

Simple Data Analysis

Unified SQL interfaces enable you to access multiple data sources.

Flexible Extensibility

openLooKeng allows you to effortlessly add connectors for new data sources,

removing the need for data migration.

Thriving openLooKeng Community



Community Members


  • OmniRuntime:Powering Next-Generation Analytics

    gravitys169 | August 6, 2021

    Modern analytics engines play a crucial role in serving businesses with real-time analysis at low latency and cost amidst data explosion in scale and variety. Moreover, present-day applications expect these systems to deliver high query concurrency and high throughput while supporting queries over both structured and unstructured data. To satisfy these requirements, modern analytics engines and databases often rely on the compilation of query plans to native code. Hand-written operators such as FILTER, GROUPBY, and JOIN, typically contain control flows required to process different parameters and data types.

  • Memory Connector: Sorting, Indexing and Spill-to-disk

    Arjun Krishna | July 20, 2021

    Improvements to openLookeng’s Memory Connector in v1.3.0, including benchmarking results

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  • openLooKeng v1.4.0 Officially Released

    openLooKeng | October 15, 2021

    In October, openLooKeng v1.4.0 is officially released with optimizations based on partners' experience and suggestions, to improve the engine performance.

  • openLooKeng v1.3.0 Official Released

    openLooKeng | June 30, 2021

    To continuously provide partners with an optimal data analysis experience, openLooKeng iterates once every three months, with the most recent version (openLooKeng v1.3.0) released in June 2021. Based on partners' experience and suggestions, we enhanced existing features, and introduced new features to improve the engine performance.

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