Apache Iceberg Explained: A Tutorial with Dremio #shorts

Apache Iceberg is a data lakehouse table format that enables data warehouse-like workloads on a data lake. This table format provides the ability to manage large datasets with a high degree of flexibility and scalability. With Apache Iceberg, you can create tables that are optimized for both read and write operations, making it an ideal tool for working with large datasets.

Apache Iceberg provides features such as schema evolution, which allows users to make changes to the structure of their tables without having to recreate them from scratch. It also supports advanced query optimization techniques such as predicate pushdown and partition pruning, which can help reduce the amount of time needed to query large datasets. Additionally, Apache Iceberg supports multiple file formats, including Parquet and ORC, allowing users to access their data in the most efficient manner possible.

Apache Iceberg is an open source project developed by the Apache Software Foundation and is designed to provide an efficient way of managing large amounts of data in a data lakehouse environment. It enables users to store and query their data quickly and efficiently while maintaining high levels of security. Apache Iceberg also offers support for different storage engines such as Hive, Presto, Impala, Kudu and Druid, making it easy for organizations to integrate their existing systems with Apache Iceberg for improved scalability and performance.

If you’re looking for a powerful tool that will enable you to manage your data lake more efficiently while providing all the features necessary for enterprise-level workloads, then Apache Iceberg is definitely worth considering. To learn more about this powerful tool from Dremio’s experts in Data Lakehouse technology, check out Dremio’s #shorts video on “What is Apache Iceberg?” and get started today!

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