GreptimeDB vs LinDB
GreptimeDB
greptime.comLinDB
lindb.ioSide by side
| Figure | GreptimeDB | LinDB |
|---|---|---|
| Price from | $290/mo | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Android | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · Time-Series Databases | 8.0 (#17) | 8.7 (#5) |
| Deployment | GreptimeDB can run standalone or as a horizontally scalable cluster, and the download page provides Kubernetes Helm charts, Docker images, and binaries. | The documentation describes standalone and cluster modes, and deployment as a binary with ETCD as its external dependency. |
| Integrations | Documented integrations include Prometheus, Grafana, Kafka, Apache Flink, Apache Spark, Telegraf, EMQX, Fluent Bit, and others. | The documentation says data ingestion currently supports FlatBuffers, Protocol Buffers, and InfluxDB protocols. |
| Product | GreptimeDB is an open-source observability database that stores and queries metrics, logs, and traces with one columnar engine and a shared SQL layer. | LinDB is an open-source, cloud-native, horizontally scalable distributed time-series database. |
| Security | The FAQ lists basic username/password authentication, user-level read/write access control, and TLS/SSL connections for open source; enterprise and cloud list RBAC, LDAP, at-rest encryption, and audit logging. | The introduction lists self-governance and defensive capability against malicious users as features. |
| Support | Enterprise includes one-on-one technical support and SLA-backed response times; open-source users get community support through Slack and GitHub. | The product page links to GitHub channels for feature requests, bug reports, and questions. |
Plans
GreptimeDB
- GreptimeDB Enterprise Fully-Managed$290 a month
- GreptimeDB Enterprise Bring Your Own CloudPriced on request
In their own words
GreptimeDB
GreptimeDB is an open-source observability database for storing and querying metrics, logs, and traces through a columnar engine and shared SQL layer. It targets append-heavy, time-indexed workloads such as observability and IoT data, rather than general-purpose transactional database work. Users can query signal tables with SQL and metrics with PromQL. Ingestion options include Prometheus Remote Write, OpenTelemetry OTLP/HTTP, Loki Push API, Elasticsearch Bulk API, InfluxDB Line Protocol, MySQL, PostgreSQL, gRPC, and HTTP. Documented integrations include Prometheus, Grafana, Kafka, Apache Flink, Apache Spark, Telegraf, EMQX, and Fluent Bit. It can run standalone or as a horizontally scalable cluster, with Helm charts, Docker images, and binaries for macOS, Linux, Windows, and Android ARM64. The open-source edition lists username/password authentication, user-level read/write access control, and TLS/SSL connections. Enterprise adds features including LDAP, fine-grained RBAC, audit logging, and encryption at rest. The fully managed Enterprise plan costs $290 a month. Open-source users receive community support through Slack and GitHub.
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.