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Analytics SDKs

Overview​

The Snowplow Analytics SDKs are designed for data engineers and data scientists working with Snowplow in a number of languages.

Some good use cases for the SDKs include:

  1. Transforming the Enriched TSV to Enriched JSON for further processing
  2. Developing AI/ML models on your event data
  3. Performing analytics-on-write in AWS Lambda as part of our Kinesis real-time pipeline
  4. Within Snowplow pipeline components to process event data

Snowplow Analytics SDKs​

  • Scala Analytics SDK - lets you work with Snowplow enriched events in your Scala event processing, data modeling and machine-learning jobs. You can use this SDK with Apache Spark, AWS Lambda, GCP Cloud Functions, Apache Flink and other Scala-compatible data processing frameworks.
  • JavaScript and TypeScript Analytics SDK - lets you work with Snowplow enriched events in your Node.js or other JavaScript environments. This SDK can be used with AWS Lambda and Google Cloud Functions.
  • Go Analytics SDK - lets you work with Snowplow enriched events in your Go environments. This SDK can be used with AWS Lambda and Google Cloud Functions.
  • Python Analytics SDK - lets you work with Snowplow enriched events in your Python event processing, data modeling and machine-learning jobs. You can use this SDK with Apache Spark, AWS Lambda, GCP Cloud Functions and other Python-compatible data processing frameworks.
  • .NET Analytics SDK - lets you work with Snowplow enriched events in your .NET event processing, data modeling and machine-learning jobs. You can use this SDK with Azure Data Lake Analytics, Azure Function, AWS Lambda, GCP Cloud Functions other .NET-compatible data processing frameworks.
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