Features

Reliable, low-latency streaming data storage
Reliable, low-latency streaming data storage

With an optimized storage engine design, HStreamDB provides low latency persistent storage of streaming data and replicates written data to multiple storage nodes to ensure data reliability.

It also supports hierarchical data storage and can automatically dump historical data to lower-cost storage services such as object storage, distributed file storage, etc. The storage capacity is infinitely scalable, enabling permanent storage of data.

Easy support and management of large scale data streams
Easy support and management of large scale data streams

HStreamDB uses a stream-native design where data is organized and accessed as streams, supporting creating and managing large data streams. Stream creation is a very lightweight operation in HStreamDB, maintaining stable read and write latency despite large numbers of streams being read and written concurrently.

The performance of HStreamDB streams is excellent thanks to its native design, supporting millions of streams in a single cluster.

Real-time, orderly data subscription delivery
Real-time, orderly data subscription delivery

HStreamDB is based on the classic publish-subscribe model, providing low-latency data subscription delivery for data consumption and the ability to deliver data subscriptions in the event of cluster failures and errors.

It also guarantees the orderly delivery of machines in the event of cluster failures and errors.

Powerful stream processing support built-in
Powerful stream processing support built-in

HStreamDB has designed a complete processing solution based on event time. It supports basic filtering and conversion operations, aggregations by key, calculations based on various time windows, joining between data streams, and processing disordered and late messages to ensure the accuracy of calculation results. Simultaneously, the stream processing solution of HStream is highly extensible, and users can extend the interface according to their own needs.

Real-time analysis based on materialized views
Real-time analysis based on materialized views

HStreamDB will offer materialized view to support complex query and analysis operations on continuously updated data streams. The incremental computing engine updates the materialized view instantly according to the changes of data streams, and users can query the materialized view through SQL statements to get real-time data insights.

Easy integration with multiple external systems
Easy integration with multiple external systems

The stream-native design of HStreamDB and the powerful stream processing capabilities built-in make it ideally suited as a data hub for the enterprise, responsible for all data access and flow, connecting multiple upstream and downstream services and data systems.

For this reason, HStreamDB also provides Connector components for interfacing with various external systems, such as MySQL, ClickHouse, etc., making it easy to integrate with external data systems.

Cloud-native architecture, unlimited horizontal scaling
Cloud-native architecture, unlimited horizontal scaling

HStreamDB is built with a Cloud-Native architecture, where the compute and storage layers are separated and can be horizontally scaled independently.

It also supports online cluster scaling, dynamic expansion and contraction, and is efficient in scaling without data repartitioning, mass copying, etc.

Fault tolerance and high availability
Fault tolerance and high availability

HStreamDB has built-in automatic node failure detection and error recovery mechanisms to ensure high availability while using an optimized consistency model based on Paxos.

Data is always securely replicated to multiple nodes, ensuring consistency and orderly delivery even in errors and failures.

Integrate with EMQ X

Integrate with EMQ X

Resources

docs

Documentation

Quickstart with Docker

Quickly install HStreamDB using Docker and learn how to create streams in HStreamDB and insert data into the stream.

Learn More →