Data Streaming Meets Data Lake and Lakehouse with Apache Iceberg and Delta Lake
Read More

Data Streaming Meets Lakehouse: Apache Iceberg for Unified Real-Time and Batch Analytics

Apache Iceberg is gaining momentum as the open table format of choice for modern data architectures. In this blog post, the key takeaways from my talk at Open Source Data Summit are shared, along with the full video and downloadable slides. The session explores how Iceberg fits into real-time data streaming with Apache Kafka and Flink, why streaming into a data lake is complex, and what patterns actually work in production. It also covers technical challenges like schema evolution, compaction, and governance — and how to solve them. Watch the session, review the slides, and learn how Iceberg helps build reliable, streaming-powered data products at scale.
Read More
Apache Iceberg Open Table Format for Data Lake Lakehouse Streaming wtih Kafka Flink Databricks Snowflake AWS GCP Azure
Read More

Apache Iceberg – The Open Table Format for Lakehouse AND Data Streaming

An open table format framework like Apache Iceberg is essential in the enterprise architecture to ensure reliable data management and sharing, seamless schema evolution, efficient handling of large-scale datasets and cost-efficient storage. This blog post explores market trends, adoption of table format frameworks like Iceberg, Hudi, Paimon, Delta Lake and XTable, and the product strategy of leading vendors of data platforms such as Snowflake, Databricks (Apache Spark), Confluent (Apache Kafka / Flink), Amazon Athena and Google BigQuery.
Read More