openLooKeng

Free plan APILinuxSelf-hosted

What openLooKeng is

openLooKeng is an open-source data virtualization engine that lets teams query multiple data sources through a unified SQL interface. It is designed to analyze data where it resides, adding sources through connectors rather than requiring data migration. The project describes joint queries across relational databases, NoSQL, Hive, and MPP data warehouses, including examples such as MySQL, Oracle, HBase, Elasticsearch, and Kafka. Geographically remote clusters can participate in a query through hierarchical deployment and cross-region query-plan optimization. Huawei describes interactive, batch, and streaming query scenarios, while noting that the first version supported interactive queries. Listed capabilities include front scheduling, cross-source indexing, dynamic filtering, cross-source collaboration, and horizontal scaling. Coordinator active-active high availability and an extensible connector framework are also described. The engine is based on the open-source Presto SQL engine for interactive query analysis and uses the Apache License 2.0. It is self-hosted, with Linux scripts for single-node and multi-node installation, including an offline option. The multi-node script requires Java newer than 1.8.0_151. Code is hosted on Gitee and GitHub.

Who it suits

It suits big-data developers and teams that need SQL analysis across varied data sources, data centers, or hybrid clouds. It is intended for organizations able to deploy and operate self-hosted Linux software.

What it does well

Free under the Apache License 2.0.
Queries data through a unified SQL interface.
Connectors add sources without data migration.
Supports geographically remote cluster queries.
Includes Coordinator active-active high availability.

What to know first

Self-hosted deployment requires operating the software.
Multi-node installation script requires Java newer than 1.8.0_151.
First version supported interactive queries.

Plans

Plan	Billed and limits	Price
openLooKeng	Apache License 2.0; self-hosted deployment	Free

As openlookeng.io lists them, read 9 Oct 2026. The maker's own page has the final word.

Getting started

Visit openlookeng.io and choose the Linux installation guide.
Select a single-node or multi-node deployment script; an offline installation option is available.
For the multi-node installation script, use Java newer than 1.8.0_151.
Configure data sources through the connector framework.
Use the ODBC driver for documented Windows client integration if needed.

Verdict

openLooKeng is aimed at cross-source analysis without moving data into one location first. Its self-hosted Linux deployment and connector framework make deployment requirements worth checking against the project’s installation guidance.

Questions

How much does openLooKeng cost?

Its listed plan is free.

Is openLooKeng open source?

Yes. The project uses Apache License 2.0.

Which platforms are listed?

The listed platforms are API, Linux, and self-hosted. The project also provides an ODBC driver for Windows 10 64-bit and Windows Server 2016 64-bit.

Can it query data without moving it?

Yes. It supports analytics where data resides, and connectors can add sources without data migration.

What query scenarios does it support?

The project describes interactive, batch, and streaming scenarios, while noting that the first version supported interactive queries.

What does the multi-node installation require?

The multi-node installation script requires Java newer than 1.8.0_151.

Facts from openLooKeng's own pages

Client integration: The project provides an ODBC driver for Windows and documents support for Windows 10 64-bit and Windows Server 2016 64-bit. · github.com, 9 Oct 2026
Connector framework: The project provides an extensible data-source connector framework. · huawei.com, 4 Oct 2026
Cross data center: It supports data analysis across data centers and hybrid clouds. · openlookeng.io, 4 Oct 2026
Data sources: The project README describes joint queries across RDBMS, NoSQL, Hive, and MPP data warehouses, with MySQL, Oracle, HBase, Elasticsearch, and Kafka as examples. · github.com, 9 Oct 2026
Deployment: The installation guide provides scripts for single-node and multi-node Linux deployments, including an offline installation option. · github.com, 9 Oct 2026
Deployment requirement: The installation guide says Java must be newer than 1.8.0_151 for its multi-node installation script. · github.com, 9 Oct 2026
Distributed queries: Geographically remote openLooKeng clusters can participate in the same query using hierarchical deployment and cross-region query plan optimization. · github.com, 9 Oct 2026
Foundation: Huawei says openLooKeng uses the open-source Presto SQL engine as its basis for interactive query analysis. · huawei.com, 4 Oct 2026
High availability: The launch announcement describes coordinator active-active support and a scalable data-source connector framework. · huawei.com, 9 Oct 2026
In-place analytics: It supports analytics on data where it resides, without requiring data migration. · github.com, 9 Oct 2026
Intended users: The launch announcement invites big-data developers to join the open-source community and describes analytics across data sources and data centers. · huawei.com, 9 Oct 2026
License: Huawei’s launch announcement states that openLooKeng is distributed under Apache License 2.0 for free use, modification, and redistribution. · huawei.com, 9 Oct 2026
No data migration: The maker says new data sources can be added through connectors without data migration. · openlookeng.io, 4 Oct 2026
ODBC security options: The ODBC guide describes connection configuration options for SSL and Kerberos. · github.com, 9 Oct 2026
Performance features: The project README describes dynamic filtering, bitmap, Bloom and min-max indexes, and metadata, execution-plan, and ORC row-data caches. · github.com, 9 Oct 2026
Product: openLooKeng is described as a high-performance data virtualization engine. · huawei.com, 4 Oct 2026
Purpose: openLooKeng is an open-source data virtualization engine for querying data across disparate sources through a unified SQL interface. · huawei.com, 9 Oct 2026
Query scenarios: Huawei describes support for interactive, batch, and streaming query scenarios, with the first version supporting interactive queries. · huawei.com, 4 Oct 2026
Query workloads: The launch announcement describes interactive, batch, and stream query scenarios, while noting that the first version supported interactive queries. · huawei.com, 9 Oct 2026
Reliability: The project provides Coordinator AA high availability. · huawei.com, 4 Oct 2026
Source code: The project lists Gitee and GitHub as code hosting locations. · huawei.com, 4 Oct 2026
SQL access: It provides a unified SQL interface for accessing multiple data sources. · openlookeng.io, 4 Oct 2026

Where openLooKeng stands on Freedom251

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