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SwiftLake: Bringing Apache Iceberg and DuckDB Together for a Smarter Data Management
Originally aired:
About the Session
Modern applications generate vast amounts of data, and traditional RDBMS-based architectures struggle to keep up with scalability, performance, and cost-efficiency demands. While object storage solutions like S3 have revolutionised data management, migrating from RDBMS to an object storage-based model is often complex and disruptive. SwiftLake bridges this gap, seamlessly transitioning from RDBMS to object storage by integrating Apache Iceberg and DuckDB in a lightweight, single-node Java library. SwiftLake enables schema evolution, hidden partitioning, time travel, and efficient caching while maintaining SQL compatibility for existing applications.
In this session, you'll learn:
- How SwiftLake simplifies the transition from RDBMS to object storage with minimal application changes
- How Apache Iceberg and DuckDB power high-performance, scalable data workloads
- How to optimize query performance, reduce costs, and maintain SLOs with efficient caching and partitioning strategies
- Join us to discover how SwiftLake enables a smarter, more cost-effective approach to data management without the complexity of distributed systems.
Target Audience
- Software Architects seeking to scale RDBMS workloads efficiently
- Software Developers aiming to optimize data costs without compromising SLOs
- Data Engineers focused on processing efficiency and reducing query latency
- Developers in high-growth environments needing flexible, scalable data architectures
SwiftLake: Bringing Apache Iceberg and DuckDB Together for a Smarter Data Management
Originally aired:
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