From Iceberg to AI: Accelerating Lakehouse & Hybrid Retrieval with Apache Doris

About this event

We're thrilled to invite you to an evening focused on the practical, real-world use of Apache Iceberg and the growing ecosystem around it.
Hosted by VeloDB, Starburst, and Confluent at the CACIB offices in Singapore.

Whether you're running Iceberg in production, exploring new architectures, or looking to connect with others solving similar data challenges, this is a great opportunity to learn and collaborate over snacks and drinks!

Session 1: Unlocking Modern Data Lakes with Starburst, Iceberg & Ozone
Speaker Bio:
Siva Periyasamy is the Head of Data Engineering and Data Platform at OCBC Bank, bringing over 25 years of experience in the banking industry with deep expertise in data and analytics.
Since joining OCBC in 2005, Siva has played a pivotal role in the bank’s data transformation journey, leading a team of data engineers, enabling them to create machine learning models and manage big data platforms.
Siva oversees OCBC’s data platform and specifically Starburst, supporting the bank’s broader machine learning and AI initiatives. His leadership has been instrumental in enabling data-driven innovation across the organization.

Session 2: Talk by Shelvia Hotama at Confluent

Session 3: From Iceberg to AI: Accelerating Lakehouse Analytics and Hybrid Retrieval with Apache Doris

Abstract:
The Lakehouse architecture, powered by open table formats such as Apache Iceberg, has become the foundation for modern analytics and AI workloads. However, efficiently serving diverse query patterns, ranging from large-scale analytical SQL to text and vector retrieval, remains a key challenge.

In this talk, we introduce how Apache Doris enhances the Iceberg-based Lakehouse with high-performance query acceleration and materialized views, enabling faster and more cost-efficient analytics directly on open data. Building on this foundation, we explore Doris for AI: a unified engine that provides seamless access to structured, semi-structured, and unstructured data through hybrid search and analytics. Doris combines analytical queries, full-text search, and vector search in a single system, making it easier to support retrieval-augmented generation (RAG) and other AI-driven applications on Lakehouse data.
Finally, we share Doris’s roadmap toward deeper integration with open table formats. This includes plans for managed Iceberg tables and bringing native inverted and vector indexing capabilities directly to Iceberg data, enabling zero-copy, high-performance analytical and retrieval workloads. The session outlines how Doris aims to bridge analytics and AI on open data, turning the Lakehouse into a truly multi-modal data foundation.

Speaker Bio:
Matt Yi is an Apache Doris PMC member and Tech VP at VeloDB. He has been deeply involved in the development of the Apache Doris project, leading and contributing to numerous core features. His work has driven significant performance enhancements and optimizations, enabling Apache Doris to excel across diverse application scenarios. With over a decade of engineering experience, Matt is also a seasoned development engineer who has previously held roles at Microsoft and other global tech leaders.

How to find us
Crédit Agricole Corporate and Investment Bank
Mapletree Business City Blk 20 West 20 Pasir Panjang Road Singapore, 117439 , Level 13