TDengine™ today released TDengine Cloud, a fully managed, open-source cloud time-series data platform. TDengine Cloud lets organizations easily start, operate, and scale the TDengine time-series data platform in AWS, Azure, and Google Cloud.
Released as open-source software in 2019, TDengine has more than 19,000 stars on GitHub and more than 154,000 instances across 50 countries worldwide. The TDengine Data Platform combines a database with caching, stream processing, and data subscription as a complete, purpose-built solution for time-series data. TDengine solves the common problem of high cardinality with a unique architecture that supports billions of data points while outperforming general-purpose and legacy time-series databases in data ingestion, querying, and compression.
“Not all companies have the expertise, time, or resources to fully support a time-series database infrastructure, especially as data continues to flood in and use cases scale,” said Jeff Tao, founder and CEO of TDengine. “TDengine Cloud enables developers to stand up a time-series data platform in seconds and removes all the ongoing operational and management burdens now and as those applications and use cases scale in the future.”
Last month, the company unveiled TDengine 3.0, delivering a fully distributed architecture with Kubernetes and container support. It decouples compute and storage resources for dynamic scaling and deployment across public, private, and hybrid clouds. TDengine Cloud brings all the advantages of TDengine 3.0 in a fully managed, cloud-native solution.
Major features and benefits of TDengine Cloud include:
- Simplified Setup and Management. With built-in caching, stream processing and data subscription, TDengine dramatically reduces the tools needed to start, operate, and manage time-series data at scale. Novel super tables provide one-time configurations of similar devices. And as a managed service, TDengine Cloud handles all clustering, backup, and data retention for easy, straightforward administration.
- Fast and Easy Data Ingestion. Users have a wide variety of choices of simplified data ingestion. This includes: writing data directly into the platform using standard SQL; leveraging a variety of connectors for popular programming languages; using an MQTT broker to send data directly to TDengine without any code; or using schemaless insert protocols.
- Easier Data Analytics and Sharing. Developers can quickly access data with connectors for Python, Java, Go, Rust, and Node.js. Dashboards and applications can simply subscribe to topics and streams, including continuous and event-driven queries for computations and alerts. And edge-to-cloud and cloud-to-cloud synchronization replicate data to every corner of the enterprise.
- Enterprise Ready. TDengine Cloud is enterprise ready with robust backup, multi-cloud replication, unlimited users, user privilege control, user action audit, VPC peering and IP whitelisting. And TDengine offers professional technical support for enterprise customers to ensure the success of your cloud service.
New users can register at https://cloud.tdengine.com for a free account and walk through a short tutorial to quickly understand the capabilities and advantages of using TDengine to unlock the power of your time-series data.
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