TDEngine is an open-source, cloud-native time-series database that’s optimized for Web of Issues (IoT), Related Automobiles, and Industrial IoT. It permits for environment friendly, real-time ingestion, processing, and monitoring of terabytes and petabytes of knowledge day by day, created by billions of sensors and knowledge collectors.
In accordance with the staff at TDEngine, this providing works to unravel the high-cardinality problem by supporting a considerable amount of knowledge assortment factors whereas additionally performing strongly by way of knowledge ingestion, querying, and compression. Â
It additionally gives a simplified answer for time-series knowledge processing on account of its built-in caching, stream processing, and knowledge subscription options. This works to scale back system design complexity in addition to operational prices.Â
Moreover, TDEngine might be deployed on public, non-public, or hybrid clouds via native distributed design, sharding and partitioning, separation of compute and storage, RAFT, assist for Kubernetes deployment, and full visibility.
The newest model of this open-source venture, TDEngine 3.0 was lately launched and brings customers a number of new updates together with:Â
- Kubernetes and serverless container assist
- Excessive scale for rising IoT and different deploymentsÂ
- Excessive efficiency on time-series knowledge
- Cach storage of recent knowledge
- Constructed-in knowledge subscription
- Simple time-series knowledge analyticsÂ
To be taught extra about this newest launch, learn the technical weblog.
