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Data Visualization

Guidelines about data analysis and visualization with CrateDB.

Apache Superset / Preset

Product

• Introduction to time series visualization in CrateDB and Apache Superset (Blog)

• Use CrateDB and Apache Superset for Open Source Data Warehousing and Visualization (Blog)

• Introduction to time series visualization in CrateDB and Apache Superset (Webinar)

• Introduction to Time-Series Visualization in CrateDB and Apache Superset (Preset.io)

Development

• Set up Apache Superset with CrateDB

• Set up an Apache Superset development sandbox with CrateDB

• Verify Apache Superset with CrateDB

Cluvio

• Data Analysis with Cluvio and CrateDB

Explo

• Introduction to Time Series Visualization in CrateDB and Explo

Grafana

• Using Grafana with CrateDB Cloud

hvPlot and Datashader

The cloud-datashader.ipynb notebook explores the HoloViews and Datashader frameworks and outlines how to use them to plot the venerable NYC Taxi dataset, after importing it into a CrateDB Cloud database cluster.

🚧 Please note this notebook is a work in progress. 🚧

Metabase

• Using Metabase with CrateDB Cloud

• Real-time data analytics with Metabase and CrateDB

pandas

• From data storage to data analysis: Tutorial on CrateDB and pandas

Plotly / Dash

• The timeseries-queries-and-visualization.ipynb notebook explores how to access timeseries data from CrateDB via SQL, load it into pandas DataFrames, and visualize it using Plotly.

  It includes advanced time series operations in SQL, like aggregations, window functions, interpolation of missing data, common table expressions, moving averages, JOINs, and the handling of JSON data.

  

• Alternatively, you are welcome to explore the canonical Dash Examples.

R

• CrateDB with R