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  1. Abstract
  2. PowerExchange for Amazon Redshift
  3. PowerExchange for Amazon S3
  4. PowerExchange for Cassandra
  5. PowerExchange for Cassandra JDBC
  6. PowerExchange for DataSift
  7. PowerExchange for Facebook
  8. PowerExchange for Google Analytics
  9. PowerExchange for Google BigQuery
  10. PowerExchange for Google Cloud Storage
  11. PowerExchange for Greenplum
  12. PowerExchange for HBase
  13. PowerExchange for HDFS
  14. PowerExchange for Hive
  15. PowerExchange for JD Edwards EnterpriseOne
  16. PowerExchange for LDAP
  17. PowerExchange for LinkedIn
  18. PowerExchange for MapR-DB
  19. PowerExchange for Microsoft Azure Blob Storage
  20. PowerExchange for Microsoft Azure Cosmos DB SQL API
  21. PowerExchange for Microsoft Azure Data Lake Store
  22. PowerExchange for Microsoft Azure SQL Data Warehouse
  23. PowerExchange for Microsoft Dynamics CRM
  24. PowerExchange for MongoDB
  25. PowerExchange for Netezza
  26. PowerExchange for Salesforce
  27. PowerExchange for SAP NetWeaver
  28. PowerExchange for Snowflake
  29. PowerExchange for Tableau
  30. PowerExchange for Teradata Parallel Transporter API
  31. PowerExchange for Twitter
  32. PowerExchange for Web Content-Kapow Katalyst
  33. Informatica Global Customer Support

PowerExchange Adapters for Informatica Release Notes

PowerExchange Adapters for Informatica Release Notes

PowerExchange for Snowflake Third-Party Limitations (10.2.2)

PowerExchange for Snowflake Third-Party Limitations (10.2.2)

The following table describes third-party known limitations:
Bug
Description
OCON-17317
When you use Snowflake jars, version 2.11-2.4.3, the performance of the read operation of a Snowflake mapping on the Spark engine drops by 1.5X when compared to Snowflake jars of version 2.11-2.3.1.
Snowflake reference number: 00034954
OCON-16276
When two Snowflake source tables contain the same column name, and you specify a Joiner condition in the Snowflake source properties, the mapping fails on the Spark engine.
OCON-12175
When you run a mapping in the native environment to read large volumes of data from Snowflake, the mapping fails with an out of memory error.
Workaround: Increase the Java heap memory size in the Data Integration Service properties, and restart the Data Integration Service.
Snowflake reference number: 00028631
OCON-11651
When you run a mapping on the Spark engine to write data of the Time data type, the Data Integration Service does not write the data to the Snowflake table even though the mapping runs successfully.
Snowflake reference number:00033380