Streaming SQL in 5 Minutes
This video walks through a tutorial on how to transform streaming data with SQL using Estuary within minutes.
0:00 Background
0:13 Use Cases
0:41 Tutorial Scenario
0:58 Estuary Tutorial Begins
1:25 GitPod
3:13 Schema Inference
3:58 Publish Catalog
5:11 Validation
Preview command to run in terminal:
flowctl preview --source flow.yaml --interval 200ms | jq -c 'del(._meta)'
Check out our in-depth article on Streaming SQL:
https://estuary.dev/streaming-sql
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While several CDC tools allow users to ingest data from a source to a target, few offer SQL transformation capabilities. Often, replicating data as-is from one place to another may not be sufficient for your needs.
For example, you may want to do some filtering, apply certain calculations to your source data, or aggregate data from multiple documents before the data arrive at the destination. Other common use cases include merging across several collections using a common key and applying business logic to the source data.
Using derivations in Estuary, you can perform a variety of transformations, from a simple remapping use case to a highly complex stateful transaction processing.
#data #datapipeline #dataengineering
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