ClickHouse/docs/en/interfaces/third-party/gui.md
Wang Fenjin a2ca0a1c5b
Add xeus-clickhouse (#12010)
xeus-clickhouse is a Jupyter kernal for ClickHouse
2020-06-28 16:42:59 +03:00

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---
toc_priority: 28
toc_title: Visual Interfaces
---
# Visual Interfaces from Third-party Developers {#visual-interfaces-from-third-party-developers}
## Open-Source {#open-source}
### Tabix {#tabix}
Web interface for ClickHouse in the [Tabix](https://github.com/tabixio/tabix) project.
Features:
- Works with ClickHouse directly from the browser, without the need to install additional software.
- Query editor with syntax highlighting.
- Auto-completion of commands.
- Tools for graphical analysis of query execution.
- Colour scheme options.
[Tabix documentation](https://tabix.io/doc/).
### HouseOps {#houseops}
[HouseOps](https://github.com/HouseOps/HouseOps) is a UI/IDE for OSX, Linux and Windows.
Features:
- Query builder with syntax highlighting. View the response in a table or JSON view.
- Export query results as CSV or JSON.
- List of processes with descriptions. Write mode. Ability to stop (`KILL`) a process.
- Database graph. Shows all tables and their columns with additional information.
- A quick view of the column size.
- Server configuration.
The following features are planned for development:
- Database management.
- User management.
- Real-time data analysis.
- Cluster monitoring.
- Cluster management.
- Monitoring replicated and Kafka tables.
### LightHouse {#lighthouse}
[LightHouse](https://github.com/VKCOM/lighthouse) is a lightweight web interface for ClickHouse.
Features:
- Table list with filtering and metadata.
- Table preview with filtering and sorting.
- Read-only queries execution.
### Redash {#redash}
[Redash](https://github.com/getredash/redash) is a platform for data visualization.
Supports for multiple data sources including ClickHouse, Redash can join results of queries from different data sources into one final dataset.
Features:
- Powerful editor of queries.
- Database explorer.
- Visualization tools, that allow you to represent data in different forms.
### DBeaver {#dbeaver}
[DBeaver](https://dbeaver.io/) - universal desktop database client with ClickHouse support.
Features:
- Query development with syntax highlight and autocompletion.
- Table list with filters and metadata search.
- Table data preview.
- Full-text search.
### clickhouse-cli {#clickhouse-cli}
[clickhouse-cli](https://github.com/hatarist/clickhouse-cli) is an alternative command-line client for ClickHouse, written in Python 3.
Features:
- Autocompletion.
- Syntax highlighting for the queries and data output.
- Pager support for the data output.
- Custom PostgreSQL-like commands.
### clickhouse-flamegraph {#clickhouse-flamegraph}
[clickhouse-flamegraph](https://github.com/Slach/clickhouse-flamegraph) is a specialized tool to visualize the `system.trace_log` as [flamegraph](http://www.brendangregg.com/flamegraphs.html).
### clickhouse-plantuml {#clickhouse-plantuml}
[cickhouse-plantuml](https://pypi.org/project/clickhouse-plantuml/) is a script to generate [PlantUML](https://plantuml.com/) diagram of tables schemes.
### xeus-clickhouse {#xeus-clickhouse}
[xeus-clickhouse](https://github.com/wangfenjin/xeus-clickhouse) is a Jupyter kernal for ClickHouse, which supports query CH data using SQL in Jupyter.
## Commercial {#commercial}
### DataGrip {#datagrip}
[DataGrip](https://www.jetbrains.com/datagrip/) is a database IDE from JetBrains with dedicated support for ClickHouse. It is also embedded in other IntelliJ-based tools: PyCharm, IntelliJ IDEA, GoLand, PhpStorm and others.
Features:
- Very fast code completion.
- ClickHouse syntax highlighting.
- Support for features specific to ClickHouse, for example, nested columns, table engines.
- Data Editor.
- Refactorings.
- Search and Navigation.
### Yandex DataLens {#yandex-datalens}
[Yandex DataLens](https://cloud.yandex.ru/services/datalens) is a service of data visualization and analytics.
Features:
- Wide range of available visualizations, from simple bar charts to complex dashboards.
- Dashboards could be made publicly available.
- Support for multiple data sources including ClickHouse.
- Storage for materialized data based on ClickHouse.
DataLens is [available for free](https://cloud.yandex.com/docs/datalens/pricing) for low-load projects, even for commercial use.
- [DataLens documentation](https://cloud.yandex.com/docs/datalens/).
- [Tutorial](https://cloud.yandex.com/docs/solutions/datalens/data-from-ch-visualization) on visualizing data from a ClickHouse database.
### Holistics Software {#holistics-software}
[Holistics](https://www.holistics.io/) is a full-stack data platform and business intelligence tool.
Features:
- Automated email, Slack and Google Sheet schedules of reports.
- SQL editor with visualizations, version control, auto-completion, reusable query components and dynamic filters.
- Embedded analytics of reports and dashboards via iframe.
- Data preparation and ETL capabilities.
- SQL data modelling support for relational mapping of data.
### Looker {#looker}
[Looker](https://looker.com) is a data platform and business intelligence tool with support for 50+ database dialects including ClickHouse. Looker is available as a SaaS platform and self-hosted. Users can use Looker via the browser to explore data, build visualizations and dashboards, schedule reports, and share their insights with colleagues. Looker provides a rich set of tools to embed these features in other applications, and an API
to integrate data with other applications.
Features:
- Easy and agile development using LookML, a language which supports curated
[Data Modeling](https://looker.com/platform/data-modeling) to support report writers and end-users.
- Powerful workflow integration via Lookers [Data Actions](https://looker.com/platform/actions).
[How to configure ClickHouse in Looker.](https://docs.looker.com/setup-and-management/database-config/clickhouse)
[Original article](https://clickhouse.tech/docs/en/interfaces/third-party/gui/) <!--hide-->