Imagine youâve got a stream of data; itâs not âbig data,â but itâs certainly a lot. Within the data, youâve got some bits youâre interested in, and of those bits, youâd like to be able to query information about them at any point. Sounds fun, right? Since I mentioned âquerying,â Iâd hazard a guess that youâve got in mind an additional datastore of some sort, whether relational or NoSQL.
But what if I told youâŚthat you didnât need any datastore other than Kafka itself? What if you could ingest, filter, enrich, aggregate, and query data with just Kafka? With ksqlDB we can do just this, and I want to show you exactly how.
In this hands-on talk weâll walk through an example of building a Telegram bot in which ksqlDB provides the key/value lookups driven by a materialised view on the stream of events in Kafka. Weâll take a look at what ksqlDB is and its capabilities for processing data and driving applications, as well as integrating with other systems.
Resources
- âď¸ Blog - Building a Telegram bot with Apache Kafka and ksqlDB
- đž Demo code
-
âď¸Confluent Cloudâď¸
Managed Apache Kafka, ksqlDB, and Schema Registry. Use code RMOFF200 when you sign up!
-
Confluent Developer
The pre-eminent resource for learning Apache Kafka. Free training courses, event streaming patterns, deep-dive articles, and language-specific client programming guides. Check it out!
- Apache Kafka 101 - free training course