Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/hstreamdb/hstream
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications.
https://github.com/hstreamdb/hstream
data-processing database distributed-database distributed-systems financial-analysis haskell hstreamdb iot iot-database kafka materialized-view real-time realtime-database scale sql stream-processing streaming streaming-data streaming-database
Last synced: 7 days ago
JSON representation
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications.
- Host: GitHub
- URL: https://github.com/hstreamdb/hstream
- Owner: hstreamdb
- License: bsd-3-clause
- Created: 2020-08-31T09:42:17.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-09-27T07:02:15.000Z (3 months ago)
- Last Synced: 2024-10-29T15:47:19.574Z (about 1 month ago)
- Topics: data-processing, database, distributed-database, distributed-systems, financial-analysis, haskell, hstreamdb, iot, iot-database, kafka, materialized-view, real-time, realtime-database, scale, sql, stream-processing, streaming, streaming-data, streaming-database
- Language: Haskell
- Homepage: https://hstream.io/
- Size: 6.27 MB
- Stars: 706
- Watchers: 24
- Forks: 55
- Open Issues: 11
-
Metadata Files:
- Readme: README.md
- Changelog: ChangeLog.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT
- Codeowners: .github/CODEOWNERS
Awesome Lists containing this project
- awesome-repositories - hstreamdb/hstream - HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications. (Haskell)
- awesome-haskell - HStreamDB - The streaming database built for IoT data storage and real-time processing. (Streaming Processing)
- awesome-streaming - HStreamDB - The streaming database built for IoT data storage and real-time processing. (Table of Contents / Streaming Engine)
- awesome-data-engineering - HStreamDB - The streaming database built for IoT data storage and real-time processing. (Stream Processing)
README
[](https://www.haskell.org/)
[](https://github.com/hstreamdb/hstream/actions/workflows/ci.yml)
[](https://hub.docker.com/r/hstreamdb/hstream)
[](https://slack-invite.hstream.io/)
[](https://twitter.com/HStreamDB)
[](https://github.com/hstreamdb/hstream/discussions)
[](https://www.youtube.com/channel/UC5FjR77ErAxvZENEWzQaO5Q)
# HStreamDB
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond.
Modernize your data stack for real-time applications.
## Main Features
- **Push real-time data to your apps**
By subscribing to streams in HStreamDB, any update of the data stream will be
pushed to your apps in real-time, and this promotes your apps to be more
responsive.
You can also replace message brokers with HStreamDB and everything you do with
message brokers can be done better with HStreamDB.
- **Stream processing with familiar SQL**
HStreamDB provides built-in support for event time-based stream processing.
You can use your familiar SQL to perform basic filtering and transformation
operations, statistics and aggregation based on multiple kinds of time windows
and even joining between multiple streams.
- **Easy integration with a variety of external systems**
With connectors provided, you can easily integrate HStreamDB with other
external systems, such as MQTT Broker, MySQL, Redis and ElasticSearch. More
connectors will be added.
- **Real-time query based on live materialized views**
With maintaining materialized views incrementally, HStreamDB enables you to
gain ahead-of-the-curve data insights that respond to your business quickly.
- **Reliable persistent storage with low latency**
With an optimized storage design based on [LogDevice](https://logdevice.io/),
not only can HStreamDB provide reliable and persistent storage but also
guarantee excellent performance despite large amounts of data written to it.
- **Seamless scaling and high availability**
With the architecture that separates compute from storage, both compute and
storage layers of HStreamDB can be independently scaled seamlessly. And with
the consensus algorithm based on the optimized Paxos, data is securely
replicated to multiple nodes which ensures the high availability of our
system.
For more information, please visit [HStreamDB homepage](https://hstream.io).
## Quickstart
**For detailed instructions, follow
[HStreamDB quickstart](https://docs.hstream.io/start/quickstart-with-docker.html).**
1. [Install HStreamDB](https://docs.hstream.io/start/quickstart-with-docker.html#installation).
2. [Start a local standalone HStream server](https://docs.hstream.io/start/quickstart-with-docker.html#start-hstreamdb-services).
3. [Start HStreamDB's interactive CLI](https://docs.hstream.io/start/quickstart-with-docker.html#start-hstreamdb-s-interactive-sql-cli)
and
[create your first stream](https://docs.hstream.io/start/quickstart-with-docker.html#create-a-stream).
4. [Run a continuous query](https://docs.hstream.io/start/quickstart-with-docker.html#run-a-continuous-query-over-the-stream).
5. [Start another interactive CLI](https://docs.hstream.io/start/quickstart-with-docker.html#start-another-cli-session),
then
[insert some data into the stream and get query results](https://docs.hstream.io/start/quickstart-with-docker.html#insert-data-into-the-stream).
## Documentation
Check out [the documentation](https://hstream.io/docs/en/latest/).
## Community, Discussion, Construction and Support
You can reach the HStreamDB community and developers via the following channels:
- [Slack](https://slack-invite.hstream.io)
- [Twitter](https://twitter.com/HStreamDB)
- [Reddit](https://www.reddit.com/r/HStreamDB)
Please submit any bugs, issues, and feature requests to
[hstreamdb/hstream](https://github.com/hstreamdb/hstream/issues).
## How to build (for developers only)
**Pre-requirements**
1. You have `python3` and `docker` installed.
2. [Optional] You can run `docker` without `sudo`. For details, see
[this docs](https://docs.docker.com/engine/install/linux-postinstall/)
3. [Optional] You can clone the GitHub repository by ssh key.
**Get the source code**
```sh
git clone --recursive [email protected]:hstreamdb/hstream.git
cd hstream/
```
**Update images**
```sh
script/dev-tools update-images
```
**Start all required services**
You must have all required services started before entering an interactive shell
to do further development (especially for running tests).
```sh
script/dev-tools start-services
```
To see information about all started services, run
```sh
script/dev-tools info
```
> _All datas are stored under `your-project-root/local-data`_
**Enter in an interactive shell**
```sh
script/dev-tools shell
```
**Build as other Haskell projects**
_Inside the interactive shell, you have all extra dependencies installed._
```
I have no name!@649bc6bb75ed:~$ cabal update
I have no name!@649bc6bb75ed:~$ make
I have no name!@649bc6bb75ed:~$ cabal build all
```
## License
HStreamDB is under the BSD 3-Clause license. See the
[LICENSE](https://github.com/hstreamdb/hstream/blob/master/LICENSE) file for
details.
## Acknowledgments
- Thanks [LogDevice](https://logdevice.io/) for the powerful storage engine.