Connect Metabase to Apache Spark, an open-source unified analytics engine
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If you’re using Apache Spark, you’re probably handling large-scale, computationally-intensive queries and need a business intelligence tool that can keep up. Maybe you’ve got A LOT of data that you need to be able to query and make sense of quickly, without lag. Metabase lets your whole team visualize and explore your data in Apache Spark with or without SQL. Run native queries on nested data and scale indefinitely.
Get business intelligence tool with friendly UX that lets everyone make sense of your data in Apache Spark.
Take control over data access and permissions to keep everyone in their own lane for maximum governance.
Put dashboards and charts in front of people with as much interactivity and room to pull threads (or as little) as you want.
Metabase runs direct queries in Apache Spark without extracts, so your reports are always up-to-date with your Apache Spark data and don’t require moving large data sets.
Self-host Metabase and Apache Spark to keep everything on your terms. Get your token and go. Both are open source, with optional cloud hosting.
Apache Spark pairs with a number of BI tools, each with their own pros and cons. Metabase is the most effective way to let everyone in the team start working with data. With a low learning curve and sophisticated but easy-to-use data tools like the Query Builder which lets people ask questions without SQL, simple drill-through, zoom-in, and breakout functionality that let people learn more from data with just a few clicks.
You can set up and connect Metabase to Apache Spark in about 5 minutes and be querying immediately, with drill-through functionality automatically generated and ready for people to start uncovering insights. Metabase is also open source and affordable, with plans and pricing that scales with you.
You can connect to Apache Spark when you’re setting up a new Metabase instance, or add a database connection any time in your admins settings:
To add a database connection, click on the gear icon in the top right, and navigate to Admin settings > Databases > Add a database.
For the full details on connecting Metabase to Apache Spark, check out our documentation.
Apache Spark permissions cannot be impersonated in Metabase (for now. This is currently possible for PostgreSQL, MySQL, and Snowflake databases).
With granular row-level permissions and user group mapping, you can effectively set up permissions to match those applied in Apache Spark.
Metabase fits with Apache Spark as a querying and visualization layer on top of your data. With Metabase you can query data in Apache Spark - with or without SQL - to create a broad range of data visualizations and types and tell a story with interactive dashboards. Viewers can filter and drill-through to get what’s most relevant, and dig deeper on what’s important to them. Visualizations and dashboards can even be shared or embedded in your app.
Apache Spark helps you analyze unstructured, semi-structured, and structured data stored in Amazon S3 - but you’ll likely need pretty advanced data and technical skills to be able to do it.
Metabase makes it possible for everyone in the team to run their own reports, without data skills or relying on someone else to write SQL for them. People used to working in Excel can leverage skills usually reserved for spreadsheets to get the answers they need from data in Apache Spark.
Metabase lets you bring together charts, visualizations, and questions into interactive dashboards that can be shared with your team and customers.
The automatically generated drill-through menu lets people click on charts to zero in on a particular category or parameter for further analysis; view individual records, or zoom in on a targeted date range. You can also add filters to let people slice the data on what’s most important to them, and add custom-click behaviors to guide data discovery (e.g. send people to a related dashboard).
