MATLAB with Databricks
Actionable insight for engineers and scientists
The MATLAB interface for Databricks® enables MATLAB® and Simulink® users to connect to data and compute capabilities in the cloud. Users can access and query big datasets remotely or deploy MATLAB code to run natively on a Databricks cluster.
Scale Big Data
Access cloud data sources through a Databricks cluster by connecting it to MATLAB with Database Toolbox™. Manipulate data remotely and use SQL to access a variety of data formats directly from cloud storage or using Delta Lake. Use Apache Spark™ SQL to access and query data sources and file types.
Use Spark Interactively with MATLAB and Databricks Connect
Incorporate Apache Spark API into MATLAB algorithms using Databricks Connect. Run your code in the cloud, exchanging data with MATLAB files and live scripts right from the MATLAB IDE and on any operating system.
Bring MATLAB to the Data
Use MATLAB Compiler™, Simulink Compiler™, and MATLAB Compiler SDK™ to package your algorithms for Databricks cluster deployment. Deployed algorithms can run as on-demand and scheduled jobs. Other Databricks users can use these algorithms and become part of data processing pipelines.
Collaborate on Data and Models Across the Enterprise
With Databricks, MATLAB and Simulink® users can access and share a variety of data, including binary, image, text, video, and more, enabling teams in engineering, business, and data analytics to interact across a single data platform.
Manage Algorithm and Model Lifecycle with MLflow
Use MLflow with MATLAB to run experiments, keep track of parameters, metrics, and code, and monitor execution results. Share your MATLAB models and discover algorithms in the model registry, saving time and allowing colleagues to benefit from your work.
Download the MATLAB Interface for Databricks
release 4.0.9
Have Questions?
Talk to a Databricks expert.
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.
