Kafka is an event hub designed to execute event streaming at high scale, with low latency and high throughput, making it a leader in the category. Many have embarked upon a Kafka implementation journey only to find that deploying this powerful, open source framework requires more coding and technical expertise than initially expected. Because Kafka is not a full, end to end ingestion solution nor does it satisfy enterprise requirements out of the box, most users focus their efforts on building a solution around Kafka instead.
Equalum’s end to end data ingestion platform is a full solution with both Kafka and Spark as part of its engine. Equalum’s no code UI offers the largest library of CDC sources available and dynamic, real-time transformation capabilities that can both accept and push data to any database, data lake, file servers or Kafka to consume. Additionally, Equalum is a fully managed, enterprise grade product, letting you easily manipulate and monitor your data throughout the ingestion process. Equalum is also a fully orchestrated solution, addressing enterprise requirements for both streaming and batch as well.
In this Office Hours, we covered:
Presenter: Alton Dinsmore, Senior Data Architect, Equalum
Alton is a data veteran (Oracle, Dell EMC, MariaDB and more) with over 40 years of design and architect experience around enterprise data solutions and applications. He has helped many companies implement successful projects around large data, high performance, large number of users, large number of transactions, clustering, as well as high availability and disaster recovery. Alton has led engineering teams, projects, and data operations, helping companies redesign or improve upon implementation to achieve their desired objectives.