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 Member



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  • 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 v1.6.0 Officially Released

    openLooKeng | March 30, 2022

    openLooKeng v1.6.0 is optimized in terms of spill to disk, low latency, connector enhancement, and task recovery, featuring higher performance and reliability and a broader space for innovation.

  • openLooKeng v1.5.0 Officially Released

    openLooKeng | December 30, 2021

    the community has attracted over 100,000 users and 2,000 pull requests, received 1,500 issues, and housed 1,500 comments. openLooKeng has been downloaded more than 100,000 times by users from 210 cities across 41 countries and regions.

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