Apache Kafka is often used alongside Elasticsearch to perform log exploration, metrics monitoring, and alerting, data visualisation, and analytics. ksqlDB is an event streaming database built on top of Apache Kafka that complements the Elasticsearch ecosystem while offering different approaches to handling certain scenarios. Both ksqlDB and Elasticsearch are powerful tools for data enrichment and transformation as well as alerting before ingestion into Elasticsearch where the search and analytics can take place. ksqlDB allows users to write SQL queries on streams from various sources, create derived streams and materialized tables, and perform database-like lookups on those materialized tables. It simplifies stream processing by providing a declarative language like SQL, making it an advantage over lower-level stream processing systems in the data ecosystem. ksqlDB can be used to build event-driven applications that transform, enrich, and react to data as it arrives, complementing Elasticsearch where data is sent for long-term storage and analytics. Typically, Kafka is deployed in front of Elasticsearch using Kafka Connect to push data from selected Kafka topics to Elasticsearch.