kdb+ vs LinDB

kdb+ is a time-series database and analytics engine from KX, built around the q vector language. It captures and analyzes real-time and historical data for time-sensitive workloads. KX describes in-memory ingestion and analysis with sub-millisecond performance. Its storage layout separates newest in-memory records in an RDB, recent disk data in an IDB, and long-term columnar archives in an HDB. Query options include q and q-SQL, with support for Python, Java, C#, C++, Rust, R, and open-source libraries. Data can arrive through tickerplants, feed handlers, batch mode, TCP/IP, Apache Kafka, or supported programming languages. KX describes applications in trading, fraud detection, and IoT monitoring across Capital Markets, Defense, and High-Tech Manufacturing. Deployments cover Linux, macOS, Windows, APIs, and self-hosted environments, with cloud documentation for AWS, Google Cloud Platform, and Microsoft Azure. SSL/TLS connections use OpenSSL certificates and keys.

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.