![]() Superset is practically the only choice for anyone wanting to deploy self-serve, customer-facing, or user-facing analytics at scale. Iceberg is a key component of many modern open data lakes.įor many years, Apache Superset has been a monster of data visualisation. ![]() Iceberg provides a high-performance table format for all of these systems while enabling full schema evolution, data compaction, and version rollback. Enter Apache Iceberg, which works with Hive, but also directly with Apache Spark and Apache Flink, as well as other systems like ClickHouse, Dremio, and StarRocks. Who cares if something “scales well” if the result takes forever? HDFS and Hive were just too damn slow. In short, if you’re looking for real-time analytics on the data lake, Hudi is a really good bet. It integrates with Apache Spark, Apache Flink, and tools like Presto, StarRocks (see below), and Amazon Athena. Apache Hudi not only provides a fast data format, tables, and SQL but also enables them for low-latency, real-time analytics. Take ad platforms for publishers, advertisers, and media buyers. When building an open data lake or data lakehouse, many industries require a more evolvable and mutable platform.
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