CnosDB vs DolphinDB

CnosDB is an open-source distributed time-series database for workloads such as IoT, industrial internet, connected vehicles, and IT operations. It supports standard SQL, time-based aggregation, and a DataFrame API. Data can be written without a predefined schema, including out of order, and historical data can be replenished. Ingestion methods include SQL, Line Protocol, OpenTSDB, Elasticsearch bulk, Loki, NDJSON, and OpenTelemetry. Deployment options include standalone, distributed, and storage-compute separated modes, on public, private, or hybrid clouds. The documentation describes horizontal scaling for storage and stateless compute nodes. Integrations include Grafana, Prometheus, Telegraf, JDBC, and a Python SDK; the open-source Python connector provides a PEP 249 interface for SQLAlchemy and pandas. Import and export formats include PARQUET, CSV, and JSON with AWS S3, Google Cloud Storage, and Azure Blob Storage. CnosDB documents retention policies, multi-tenancy, and role-based permissions, as well as optional TLS certificate and private-key settings. Community Edition is free under AGPL-3.0.

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.