DolphinDB vs FiloDB
DolphinDB
dolphindb.comFiloDB
github.comSide by side
| Figure | DolphinDB | FiloDB |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · Time-Series Databases | 8.2 (#11) | 8.1 (#12) |
| Deployment | The maker describes cloud, on-premise, and hybrid deployment options with horizontal cluster scaling. | FiloDB is deployed as standalone processes in a cluster and requires Java, Cassandra, Kafka, Rust, and a C compiler to build; SBT is also listed as a build prerequisite. |
| Product | DolphinDB is a real-time analytics and stream-processing platform powered by a high-performance time-series database. | FiloDB is an open-source distributed, real-time, in-memory time-series, event, and operational database with Prometheus query support. |
| Support | The Enterprise Trial listing includes expert technical support. | The repository invites contributions; it does not state a paid support plan on the README page. |
| Use cases | The maker describes use in finance, energy, power, transportation, industrial manufacturing, and scientific research. | Documented uses include operational metrics, distributed tracing storage, ad-hoc application-metric debugging, and real-time event storage and querying. |
Plans
In their own words
DolphinDB
DolphinDB is a real-time analytics and stream-processing platform built around a high-performance time-series database. Its storage engines cover time-series databases, OLAP and in-memory OLTP workloads, with more than 1,500 built-in analytical functions and more than 10 streaming engines. Batch and stream processing can use the same metric expression. Programming options include imperative, vectorized, functional and SQL paradigms. The distributed system supports horizontal scaling, load balancing, fault tolerance, distributed transactions and high availability across data nodes, controllers, streaming and API clients. Deployment options include cloud, on-premise and hybrid environments. Listed use cases span finance, energy, power, transportation, industrial manufacturing and scientific research. The Community Edition has a free perpetual license, limited to two nodes, each with two CPU cores and 8 GB RAM. A free Enterprise Trial supports high-availability clusters and includes expert technical support. Related components include Swordfish for embedded use, Shark for GPU workloads, Starfish for quantitative research workflows and Octopus for complex event processing. The product is available through API, extension, Linux, self-hosted, web and Windows options.
FiloDB
FiloDB is a free, Apache-2.0 open-source database for distributed, real-time time-series, event, and operational data. It is designed to ingest and query many millions of time series, sharding data across processes with distributed querying. Columnar compression and off-heap memory management support substantial in-memory storage while reducing garbage collection. PromQL is available through an HTTP API and command-line interface; the README describes support as about 60%. Histograms are a first-class column type, with the project reporting possible compression and query-speed improvements of up to two orders of magnitude. Typical ingestion uses Apache Kafka, while the Gateway accepts Influx Line Protocol over TCP. Grafana can connect through the Prometheus-compatible API, and Cassandra is identified as the persistence store. Deployment uses clustered standalone processes and requires Java, Cassandra, Kafka, Rust, a C compiler, and SBT to build.