TDengine 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.