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

Every data-driven organization has operational and analytical workloads. A best of breed approach emerges with various data platforms, including data streaming, data lake, data warehouse and lakehouse solutions and cloud services. 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 while providing strong support for ACID transactions and time travel queries. This blog post explores market trends, adoption of table format frameworks like Iceberg, Hudi, Paimon, Delta Lake, 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.

(Originally posted on Kai Waehner’s blog: “Apache Iceberg — The Open Table Format for Lakehouse AND Data Streaming”… Join the data streaming community and stay informed about new blog posts by subscribing to my newsletter)

What is an Open Table Format for a Data Platform?

An open table format helps in maintaining data integrity, optimizing query performance, and ensuring a clear understanding of the data…