3 Key Advantages of Using Java User-Defined Functions (UDF) for Snowflake with Informatica
Snowflake recently announced the availability of Snowpark and Java functions in preview for all customers on AWS.
These two new features are a bridge into the data engineering world and data programmability. They open up Snowflake Data Cloud to additional personas such as data scientists and Java developers. And they invite engineers to use the language of their choice (e.g., Scala, Java) to interact with Snowflake and leverage the power of Snowflake Data Cloud.
With Java UDF, you can bring your own custom code and business logic to Snowflake and execute it in Snowflake, close to the data, while improving performance and optimizing costs.
Developers can continue to use their existing development environment to write their complex, custom logic, load it to Snowflake Data Cloud, register it as a function, and have it available to be used by any SQL user.
As members in the Snowpark Accelerated program, Informatica has announced support for Snowflake’s Java UDF via Informatica Cloud Data Management platform.
Informatica enables customers to leverage the power of Java UDF from within Informatica’s platform as part of a complete, cloud-native data management strategy for scaling Snowflake Data Cloud analytics and applications.
Benefits for Data Integration and ELT
With this announcement, Informatica customers can combine the benefits of Java UDF with the benefits and strengths of Informatica Intelligent Data Management Cloud while they continue to use a single, unified data integration platform.
Developers can invoke their custom code from within the data integration pipeline, incorporate it into a single end-to-end flow and push it to be executed in Snowflake Data Cloud, close to their data. When large data volumes are involved, you can get significant performance gain by pushing the computation and processing close to the data.
Whether it is Java code that holds a proprietary, complex price calculation or your custom data quality and data validation logic that is too complex to achieve in SQL, you can now wrap it as a Java UDF and have it invoked from within your data integration pipeline as a simple function.
- Currently, users can select the source type as a query in a mapping and invoke a Java UDF from within it, as shown in the screen shot below.
- In the future, users will be able to invoke the Java UDF using a midstream SQL transformation
3 Key Advantages of Using Java UDF for Snowflake via Informatica Intelligent Data Management Cloud
With this announcement, customers can now:
- Continue using their existing business logic via Java UDF while using Informatica enterprise-grade orchestration and governance by allowing those functions to be integrated into their data integration pipelines.
- Leverage Snowflake’s powerful engine for a broader set of use cases and extend the types of workloads that can be designed by using Informatica and executing directly on Snowflake.
- Improve team productivity by allowing developers to use same tools and language that they are used to. In addition, this capability opens Snowflake Data Cloud for different type of users, such as data scientists, data engineers, and enables you to incorporate their code into your overall data integration flow.
Informatica is excited to support Snowflake’s Java UDF. Our combined solutions simplify the lives of data engineers and data scientists and bring more data pipelines into Snowflake Data Cloud.