openLooKeng vs PGSpider
openLooKeng
openlookeng.ioPGSpider
github.comSide by side
| Figure | openLooKeng | PGSpider |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Federation Software | 8.3 (#5) | 7.6 (#12) |
| 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. | The README demonstrates PostgreSQL and SQLite and lists PostgreSQL, MySQL, Oracle, GridDB, PGSpider, InfluxDB v2.0, and Amazon S3 Parquet storage for migration. |
| Deployment | The installation guide provides scripts for single-node and multi-node Linux deployments, including an offline installation option. | The README documents building from source and installing to /usr/local/pgspider. |
| License | Huawei’s launch announcement states that openLooKeng is distributed under Apache License 2.0 for free use, modification, and redistribution. | The included license permits use, copying, modification, and distribution without a fee, and disclaims warranties and an obligation to provide support or updates. |
| Purpose | openLooKeng is an open-source data virtualization engine for querying data across disparate sources through a unified SQL interface. | PGSpider is a SQL cluster engine for distributed big data that accesses data sources through Foreign Data Wrappers. |
Plans
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.