FiloDB vs LinDB
FiloDB
github.com
LinDB
lindb.ioSide by side
| Figure | FiloDB | LinDB |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Time-Series Databases | 8.1 (#12) | 8.7 (#5) |
| 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. | The documentation describes standalone and cluster modes, and deployment as a binary with ETCD as its external dependency. |
| 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 says data ingestion currently supports FlatBuffers, Protocol Buffers, and InfluxDB protocols. |
| Product | FiloDB is an open-source distributed, real-time, in-memory time-series, event, and operational database with Prometheus query support. | LinDB is an open-source, cloud-native, horizontally scalable distributed time-series database. |
| Support | The repository invites contributions; it does not state a paid support plan on the README page. | The product page links to GitHub channels for feature requests, bug reports, and questions. |
| Use cases | Documented uses include operational metrics, distributed tracing storage, ad-hoc application-metric debugging, and real-time event storage and querying. | The documentation describes LinDB for IoT and IT operations monitoring, including metric storage and analysis for IaaS, PaaS, SaaS, and application layers. |
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.
LinDB
LinDB is an open-source distributed time-series database for IoT and IT operations monitoring. It stores and analyzes metrics across IaaS, PaaS, SaaS and application layers, using a schema-free model of metrics, tags and fields. LinQL provides SQL-like syntax for queries and cluster or database operations; data can be inserted and queried through an HTTP REST API, client connections and an admin console. Ingestion supports FlatBuffers, Protocol Buffers and InfluxDB protocols, with Go and Java client libraries listed. The system separates computation from storage and identifies ETCD as its only external dependency. It supports replicas, horizontal scaling, operation across multiple IDCs, and automatic minute, hour and day rollups. Deployment documentation covers standalone and cluster modes, with packages for Linux, Windows and macOS and a Docker guide for Linux. LinDB is free under Apache 2.0. Its data scope is limited to numeric time series with accuracy up to the second; it is not suited to text records or finer time precision.