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https://github.com/datainsider-co/rocket-bi
A free, open-source, web-based self-service BI tailor-made for clickhouse, google bigquery, mysql, postgresql, vertica
https://github.com/datainsider-co/rocket-bi
analytics bigdata bigquery bussiness-intelligence clickhouse dashboard data etl hacktoberfest hacktoberfest2023 ingestion mysql postgresql vertica
Last synced: 6 days ago
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A free, open-source, web-based self-service BI tailor-made for clickhouse, google bigquery, mysql, postgresql, vertica
- Host: GitHub
- URL: https://github.com/datainsider-co/rocket-bi
- Owner: datainsider-co
- License: gpl-3.0
- Created: 2022-09-21T14:19:13.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-11-21T14:24:50.000Z (2 months ago)
- Last Synced: 2025-01-13T04:05:31.875Z (13 days ago)
- Topics: analytics, bigdata, bigquery, bussiness-intelligence, clickhouse, dashboard, data, etl, hacktoberfest, hacktoberfest2023, ingestion, mysql, postgresql, vertica
- Language: TypeScript
- Homepage: https://rocket.bi
- Size: 69.5 MB
- Stars: 106
- Watchers: 3
- Forks: 30
- Open Issues: 15
-
Metadata Files:
- Readme: README.md
- Contributing: contributing.md
- License: LICENSE
Awesome Lists containing this project
- awesome-clickhouse - datainsider-co/rocket-bi - Rocket BI is a web-based self-service business intelligence tool designed for analytical databases including ClickHouse. (Integrations / Data Visualization and Analysis)
README
# Rocket BI
RocketBI is a self-service, web-based business intelligent product tailor-made for analytical databases. RocketBI is the
core product of DataInsider stack. You can use RocketBI to analyze, visualize, and easily collaborate with your friends.
To learn more about DataInsider's stack and RocketBI's features, see our documentation.
You could try the demo version at https://demo.rocket.bi
### Get started
#### Run RocketBI locally:
To try out RocketBI on your machine, the best way is using our pre-built Docker images.
Prerequisites:
- docker engine 19.0+
- docker-compose 2.0+
##### 1. Prepare
*1.1. Download docker-compose file:*
```bash
mkdir rocket-bi && cd rocket-bi
wget https://raw.githubusercontent.com/datainsider-co/rocket-bi/main/docker/docker-compose.yml
```
*1.2. (Optional) Install sample clickhouse:*
If you don't have clickhouse access at the moment, you can still try RocketBI by installing our sample clickhouse
instance by running the following commands:
```bash
wget https://raw.githubusercontent.com/datainsider-co/rocket-bi/main/docker/sample_clickhouse_cluster.zip
unzip sample_clickhouse_cluster.zip
cd sample_clickhouse_cluster/
docker-compose up -d
./import_sample_data.sh
cd -
```
**NOTE:** If you're installing RocketBI on the same host with your clickhouse-server, please use `172.17.0.1` as your
CLICKHOUSE_HOST instead of `localhost` for docker to resolve hosts correctly.
##### 2. Start RocketBI
```bash
docker-compose up -d
```
##### 3. Explore your data
- Open browser and go to [localhost:5050](http://localhost:5050) to enter the web UI.
- Login to RocketBI with this default account:
```markdown
username: [email protected]
password: 123456
```
- Setup your data connection. RocketBI support multiple connectors such as Clickhouse, BigQuery, Vertica, MySql...
- Begin by creating a dashboard and using drag-n-drop tool to explore your data.
#### Build from source:
##### Server services:
Prerequisites:
- java 8
- maven 3
- mysql 5.7
- ssdb 1.9.9
```bash
git clone https://github.com/datainsider-co/rocket-bi.git
cd rocket-bi-server
# install needed libraries:
./libs/install.sh
# build source:
mvn package
# config mysql and ssdb host/port (default port for mysql is localhost:3306 and for ssdb is localhost:8888):
vi conf/local.conf
# start service locally:
./runservice start local
```
Services will be start at specific port specify in `conf/local.conf` file. For example, the default http port for
bi-service is 8080, to test if bi-service is up and running, run:
```bash
curl localhost:8080/ping
```
To stop a service, run:
```bash
./runservice stop
```
##### Rocket-bi web UI:
Prerequisites:
- node v12.22.9
- yarn 1.22.19
Start building web client by running:
```bash
cd rocket-bi-web
yarn serve
```
Web will be served at port 8080.
### Documentation
For the complete documentation visit [datainsider.co](https://docs.datainsider.co/).
### Contribute
For contribution guidelines, see [contributing](/contributing.md).
### Questions? Problems? Suggestions?
* To report a bug or request a feature, create an
[Issue](https://github.com/datainsider-co/rocket-bi/issues/new). Please make it easy for people to reproduce your
issue.
### Example
**Adhoc-Query:** Using SQL to do complex analysis & visualise the result with just drag-n-drop for a clear perspective.
There are also supported functions & autocompletion for SQL query.
**Drag-n-Drop Chart Builder:** Users can efficiently perform drag-and-drop actions to create charts and fully
customisable informative reports with a wide range of easy-to-use and flexible settings options.
**Interactive Dashboard:** Help users visualise data, simply click to dig deeper into the underlying data and filter
operational information so that data can be viewed from different perspectives or in more detail.
**Apply filter to Dashboard:** Using a dashboard filter, users can quickly apply different data viewpoints to a single
dashboard rather than creating additional dashboards.
**Add Control to Chart:** Help users dynamically change the metrics to view multiple fields applied to that property
with a simple click instead of creating multiple charts.
**Drilldown your data:** By clicking on a metric in a chart, users can quickly take a deep dive into a dataset to
explore detailed information from various perspectives.
**No Code ETL data:** With our branded no-code data modeling, business users can load, transform & extract data without
writing a single line of code.
**Row-Level Security:** Limit a user's access to certain data, define filters for each Attribute Value, and restrict
data access to query and view at the row level.
**Share & Collaboration:** Share with the rest of your organisation by granting access or providing links to them.
**Calculated & Measurement Fields:** Create a dynamic data view by using existing database fields and applying
additional logic.
**Create Relationship:** Click and connect relationships from multiple tables, and do cross sources analysis.
**Schema Management with Data Encryption:** Collect, store, and utilise data in a cost-effective, efficient, and secure
manner
