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