![]() ![]() The final business applications are in this swim lane. Based on Delta Sharing, the Databricks Marketplace is an open forum for exchanging data products. ![]() Operational databases: External systems, such as operational databases, can be used to store and deliver final data products to user applications.Ĭollaboration: Business partners get secure access to the data they need through Delta Sharing. All data science and MLOps workflows are best supported by MLflow.įor DWH and BI use cases, the Databricks lakehouse provides Databricks SQL, the data warehouse powered by SQL warehouses and serverless SQL warehouses.įor machine learning, model serving is a scalable, real-time, enterprise-grade model serving capability hosted in the Databricks control plane. Powered by Apache Spark and Photon, the Databricks Data Intelligence Platform supports both types of workloads: SQL queries via SQL warehouses, and SQL, Python and Scala workloads via workspace clusters.įor data science (ML Modeling and Gen AI), the Databricks AI and Machine Learning platform provides specialized ML runtimes for AutoML and for coding ML jobs. ![]() The Databricks lakehouse uses its engines Apache Spark and Photon for all transformations and queries.ĭue to its simplicity, the declarative framework DLT ( Delta Live Tables) is a good choice for building reliable, maintainable, and testable data processing pipelines. Streaming sources can be sensors, IoT, or change data capture processes.ĭata is typically stored in the cloud storage system where the ETL pipelines use the medallion architecture to store data in a curated way as Delta files/tables.
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