Choose a Design Pattern for Your Data Pipeline
StreamSets has created a library of free data pipelines for the most common ingestion and transformation design patterns.
- Dev data origin with sample data for testing
- Drift synchronization for Apache Hive and Apache Impala
- MySQL and Oracle to cloud change data capture pipelines
- MySQL schema replication to cloud data platforms
- Machine learning data pipelines using PySpark or Scala
- Slowly changing dimensions data pipelines
Why Use Sample Data Pipelines?
With pre-built data pipelines, you don’t have to spend a lot of time building a pipeline to find out how it works. StreamSets has created a rich data pipeline library available inside of both StreamSets Data Collector and StreamSets Transformer or from Github. Simply choose your design pattern, then open the sample pipeline. Add your own data or use sample data, preview, and run.
StreamSets smart data pipelines use intent-driven design. That means the “how” of implementation details is abstracted away from the “what” of the data, and it becomes easy to convert sample data pipelines into essential data pipelines. Instead of rewriting the same pipeline over and over, let StreamSets do the work. You’ve got more important problems to solve.