Table of Contents

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  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Databricks Delta Lake

Databricks Delta Lake

You can use Databricks Delta Lake as a target in mappings.
Delta Lake is a data lake resource that stores data in large tables. Databricks uses proprietary Delta software to manage stored data and allow fast access to the data. Delta Lake supports ACID transactions.
Mappings can access Delta Lake resources on the AWS or Azure platforms. You can access Delta Lake tables built on top of any of the following storage types:
  • Azure blob storage
  • Azure Data Lake Storage (ADLS) Gen1 or Gen2
  • Amazon Web Services (AWS) S3.
To use Delta Lake resources in a mapping, create a relational data object and use a JDBC connection to connect to the resource.
To perform data ingestion to a Delta Lake target, use a pass-through mapping with a flat file source.


Updated September 28, 2020