A recent webcast discussed how modern enterprises can adopt new data management tools to manage large datasets. It demonstrated the use of Apache Kafka and SingleStore to build interactive, real-time data pipelines that capture, process, and serve massive amounts of data to millions of users. The webcast covered various questions from attendees, providing answers on topics such as SingleStore's database type (modern in-memory optimized), minimum memory requirements, JSON support, infrastructure requirements, and how to handle schema changes, ingest complex master detail records, and use user-defined decoding. It also compared the advantages of using Apache Kafka versus Amazon S3 for data ingestion. The webcast provided examples of SingleStore Pipelines with Python scripts for transforming JSON messages and ingesting data from Apache Kafka. Additionally, it discussed how SingleStore handles back-pressure automatically and offers a Quick Start Guide to get started with Apache Kafka and SingleStore.