3 posts tagged with "Data Lakehouse"

Apache Hive and Apache Iceberg represent two different generations of the data lake ecosystem. Hive was born in the Hadoop era as a SQL abstraction over HDFS, excelling in batch ETL workloads and still valuable for organizations with large Hadoop/ORC footprints. Iceberg, by contrast, emerged in the cloud-native era as an open table format designed for multi-engine interoperability, schema evolution, and features like time travel. If you are running a legacy Hadoop stack with minimal need for engine diversity, Hive remains a practical choice. If you want a flexible, future-proof data lakehouse that supports diverse engines, reliable transactions, and governance at scale, Iceberg is the more strategic investment.

Akshay Kumar Sharma

Sep 15, 2025

Deploy a complete, production-ready OLake data replication platform on Kubernetes in minutes using the official Helm chart. Covers architecture, quickstart, and production guidance.

Schitiz Sharma

Aug 29, 2025

Compare Apache Iceberg and Delta Lake for batch analytics and ML pipelines. Learn about performance, ecosystem integration, and when to choose each format.

Shubham Satish Baldava

Jul 31, 2025