anchor.diff:  :awestruct-tags: [ mysql, postgres, elasticsearch, smt, example ]
   :awestruct-layout: blog-post
   
  -We have seen how to stream a change data to a downstream database link:/blog/2017/09/25/streaming-to-another-database[few weeks ago].
  -
  -In this blog post we will follow the same approach to stream the data to an https://www.elastic.co/[Elasticsearch] engine for potential further search processing. But to make the matter a little bit more interesting we will stream the data to both PostgreSQL database and Elasticsearch so we will optimize access to data both via SQL query language and a full-text search.
  +We have seen how to stream a change data changes to a downstream database link:/blog/2017/09/25/streaming-to-another-database[few weeks ago].
  +
  +In this blog post we will follow the same approach to stream the data to an https://www.elastic.co/[Elasticsearch] server for potential further search processing. But to make the matter a little bit more interesting we will stream the data to both PostgreSQL database and Elasticsearch so we will optimize access to data both via SQL query language and a full-text search.
   
   == Topology
   The general topology for this scenario is displayed on the following picture:
  
positive.code: 
  &nbsp; +
  
  We are going to simply the deployment again, so we will use only one Kafka Connect instance that will contain all connectors and will serve as bot an event producer and consumer.
  
  &nbsp; +
  
  
negative.code: docker-compose up
  ----
  
  When all components are started we are going to register the Elasticsearch Sink connector writing into the Elasticsearch instance.
  We want to use the same key (primary id) in the source and both PostgreSQL and Elasticsearch.
  [source,bash,indent=0]
  ----
  