DolphinDB vs LinDB
DolphinDB
dolphindb.com
LinDB
lindb.ioSide by side
| Figure | DolphinDB | LinDB |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · Time-Series Databases | 8.2 (#11) | 8.7 (#5) |
| Deployment | The maker describes cloud, on-premise, and hybrid deployment options with horizontal cluster scaling. | The documentation describes standalone and cluster modes, and deployment as a binary with ETCD as its external dependency. |
| Product | DolphinDB is a real-time analytics and stream-processing platform powered by a high-performance time-series database. | LinDB is an open-source, cloud-native, horizontally scalable distributed time-series database. |
| Security | The maker documents user and group access controls, multiple privilege types, function views, RSA encryption, and HTTPS support. | The introduction lists self-governance and defensive capability against malicious users as features. |
| Support | The Enterprise Trial listing includes expert technical support. | The product page links to GitHub channels for feature requests, bug reports, and questions. |
| Use cases | The maker describes use in finance, energy, power, transportation, industrial manufacturing, and scientific research. | 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
DolphinDB
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.
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.