Apache IoTDB vs FiloDB

Apache IoTDB is an open-source industrial IoT time-series database for collecting, storing, managing, and analyzing device data across edge and cloud deployments. The project describes high-speed writes for millions of networked devices alongside fast reads. Query features include aligning time across devices and sensors, time-series computation, and aggregation by time dimensions. Ingestion options include IoTDB-SQL, JDBC, Java, C++, Python, and Go native APIs, REST, MQTT, CSV, and TsFile. Named analysis ecosystem examples include Hadoop, Spark, Flink, and Grafana. Deployment options include cloud installation, a desktop terminal tool, and synchronization between cloud and on-premise machines. The REST service is disabled by default and uses Basic Authentication except for the health check endpoint. Data and cluster permissions can be managed through users, roles, and privileges. The homepage states disk storage can cost less than $0.23 per GB. The project lists energy, aerospace, transportation, steel, and other IoT scenarios. Its JDBC documentation cautions that insert operations may not provide high-performance writing and recommends the Java Native API for Java applications.

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.