FiloDB vs Gnocchi
FiloDB
github.com
Gnocchi
gnocchi.osci.ioSide by side
| Figure | FiloDB | Gnocchi |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 0 |
| Spec score · Time-Series Databases | 8.1 (#12) | 7.7 (#21) |
| Deployment | 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. | Gnocchi can be installed with pip, from source, using Docker, or using OpenShift. |
| Integrations | The README describes using FiloDB as a Grafana data source through its Prometheus-compatible HTTP API and identifies Cassandra as its persistence store. | The documentation lists support for Grafana, Prometheus Remote Write, Nagios/Icinga, StatsD, Collectd, InfluxDB line protocol, and AMQP 1.0. |
| Product | FiloDB is an open-source distributed, real-time, in-memory time-series, event, and operational database with Prometheus query support. | Gnocchi is an open-source time series database for storing and indexing time series data and resources at large scale. |
| Storage | Columnar compression and off-heap memory management help it store substantial data in memory while reducing garbage collection. | Documented storage options include file, Ceph, OpenStack Swift, Amazon S3, and Redis; Ceph is described as the recommended driver. |
| Support | The repository invites contributions; it does not state a paid support plan on the README page. | The project documentation points users to its source code, GitHub bug tracker, and the #gnocchi IRC channel on OFTC. |
Plans
In their own words
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.