The MATLAB Interface for Databricks® enables you to connect to data and compute capabilities in the cloud. You can access and query big datasets remotely or deploy MATLAB code to run on a Databricks cluster.
- Use SQL to work with data in Databricks
- Work with Spark™ interactively in MATLAB
- Run compiled MATLAB algorithms on Databricks
- Share MATLAB algorithms with other Databricks users working with Python®
Access Big Data with SQL
Access cloud data sources through a Databricks cluster by connecting it to MATLAB with Database Toolbox. Manipulate data remotely and use SQL to access tabular data on Databricks. Use Apache® Spark™ SQL to query data in Spark workflows.
Use Spark with MATLAB and Simulink
Incorporate Apache Spark API commands into MATLAB algorithms using Databricks Connect. The Spark API commands execute on a Databricks cluster, including serverless clusters.
Deploy MATLAB to the Data
Use MATLAB Compiler SDK and Simulink Compiler to package your algorithms for Databricks cluster deployment using MATLAB Runtime. Deployed algorithms can run in notebooks or as on-demand and scheduled jobs. You can use these algorithms and become part of data processing pipelines.
Programmatically Interact with Databricks
The REST API enables you to programmatically interact with the Databricks environment from MATLAB, for example, to control jobs or clusters within Databricks.
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Use SQL to work with Databricks data
Send queries and manipulate data in the cloud with SQL. Use MATLAB Database Toolbox™ or Spark SQL to read data from Databricks tables, Databricks-connected data sources, and various file types. Create your own tables in multiple file formats or use Databricks Delta Lake tables and Delta Lake. Query results are converted to MATLAB tables, which are directly usable in MATLAB toolboxes and algorithms. Create your own cloud-enabled algorithm, too.
Work with cloud data interactively in MATLAB with Databricks Connect and DBFS
Explore your data on the cloud using DBFS. Create, upload, download, and organize files like you would locally – all from MATLAB. With Databricks Connect, work directly with Spark in the cloud from your desktop. Work with large datasets and leverage Spark’s scalability and speed. Download data samples as you refine your algorithm, and train and test your AI models locally, before deploying them to run on complete datasets in the cloud.
Run your MATLAB algorithms natively on Databricks Spark Clusters
Using the MATLAB Compiler and MATLAB Compiler SDK, execute your MATLAB code as a Spark Submit job. When deployed to a MATLAB Runtime-enabled Databricks cluster, your MATLAB algorithm can scale to any number of nodes. Run your MATLAB jobs ad-hoc or on an automated schedule. Enable your MATLAB algorithms to leverage the parallel processing power of Spark and accelerate data processing in the cloud.
Share MATLAB algorithms with other Databricks users
Once MATLAB algorithms are deployed to Databricks, share them with other users and incorporate them into multistep workflows. Deploy and execute MATLAB algorithms natively as jobs, at scale, or on MATLAB Runtime-enabled clusters.
Deploy MATLAB code as a library or a user-defined function for use in any language, including SQL scripts. Java or Python libraries and notebooks can also use this code.
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