openLooKeng vs Stardog
openLooKeng
openlookeng.io
Stardog
stardog.comSide by side
| Figure | openLooKeng | Stardog |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 5 |
| Spec score · Data Federation Software | 8.3 (#5) | 8.4 (#4) |
| Deployment | The installation guide provides scripts for single-node and multi-node Linux deployments, including an offline installation option. | Stardog can run as a managed AWS cloud service, in customer cloud environments, or on premises through Docker, Kubernetes, AWS Marketplace, and Azure Marketplace. |
| License | Huawei’s launch announcement states that openLooKeng is distributed under Apache License 2.0 for free use, modification, and redistribution. | Stardog Free is proprietary, licensed software and the pricing FAQ explicitly says it is not open source. |
| Purpose | openLooKeng is an open-source data virtualization engine for querying data across disparate sources through a unified SQL interface. | Stardog connects enterprise data into a semantic layer for AI, analytics, search, and applications. |
Plans
Stardog
- Stardog Cloud FreeFree
- Stardog FreeFree
- Stardog FreeFree
- Stardog Cloud EnterprisePriced on request
- Stardog EnterprisePriced on request
In their own words
openLooKeng
openLooKeng is a free, open-source data virtualization engine that lets teams query disparate systems through one SQL interface. It analyzes data where it resides, adding sources through connectors without requiring migration. Listed examples span relational databases, NoSQL systems, Hive, MPP warehouses, MySQL, Oracle, HBase, Elasticsearch, and Kafka. Queries can involve data centers, hybrid clouds, and geographically remote clusters using hierarchical deployment and cross-region plan optimization. Huawei describes interactive, batch, and streaming workloads, while noting that the first version supported interactive queries. Features include front scheduling, cross-source indexing, dynamic filtering, cross-source collaboration, horizontal scaling, and Coordinator active-active availability. The project is based on the open-source Presto SQL engine and uses Apache License 2.0. It is self-hosted, with Linux scripts for single-node, multi-node, and offline installation. Windows clients can connect through an ODBC driver supporting Windows 10 64-bit and Windows Server 2016 64-bit.