Next-Generation Data Lakehouse Using Open-Source Solutions

Unified lakehouse architectures have emerged in response to surging data volumes and the growing need for real-time, scalable analytics, merging the strengths of data lakes and warehouses. This chapter introduces a next-generation lakehouse solution built on open-source table formats like Delta Lake, Apache Hudi, and Apache Iceberg for robust governance, ACID transactions, schema evolution, and time travel. It leverages open-source distributed SQL querying engines like Presto and Trino for low-latency, complex analytics over heterogeneous data sources. The architecture features a layered design with specialized table formats optimized for diverse workloads, a unified metadata catalog for seamless data access, and scalable query engines for efficient analytics. The open-source, modular architecture provides resilience and scalability, empowering organizations to build flexible, AI-enabled data pipelines tailored to evolving, dynamic business needs, outperforming proprietary, well-known cloud-based solutions such as AWS Redshift, Azure Synapse, Google BigQuery, and third-party platforms like Databricks and Snowflake.