Real-Time Data Engineering Decoded: Storage, ETL & OLAP in One Live Session

Traditional batch-oriented pipelines and fragmented data stacks are struggling to keep up with the demands of modern, real-time analytics. High query latency, complex ETL maintenance, and spiraling infrastructure costs often hold enterprise data teams back.

Join us for a hands-on joint webinar where we decode the modern real-time data stack. In this session, our industry experts will dive deep into the transition from legacy batch processing to modern real-time architecture, explore the inner mechanics of VeloDB's storage and execution engine, and showcase a live hands-on demonstration.

What We Will Cover

Part 1: The Modern Analytics Landscape (Presented by Aruneswaran A B, GeoPITS)

• Data Engineering Challenges in Modern Analytics: Overcoming the limitations of traditional batch-oriented pipelines and fragmented architectures.
• Real-Time Analytics vs. Traditional Batch: A deep-dive performance comparison focusing on query latency, ingestion throughput, and total cost of ownership (TCO).

Part 2: Deep Dive into VeloDB Architecture & Hands-On Demo (Presented by Shilin Wu, VeloDB)

• Introducing VeloDB: Core engine design, Massively Parallel Processing (MPP) execution, vectorized processing, and unified analytics.
• VeloDB Storage Architecture: Exploring the hybrid row-columnar storage model, tiered storage strategies, and compaction mechanics.
• ETL, Data Sync & OLAP: Seamless data ingestion, Change Data Capture (CDC), federated lakehouse queries, and query execution internals.
• Live Demonstration: Walkthrough of architecture, storage behavior, real-time data loading, and query performance.

Part 3: Interactive Q&A

• Live open discussion with our speakers to address your specific architectural and operational questions.

Speakers

Aruneswaran A B Database & Data Engineering Specialist @ GeoPITS With over 4 years of experience in database and data engineering, Aruneswaran specializes in building scalable data solutions across Databricks, AWS, Oracle, Microsoft SQL Server, and Snowflake. At GeoPITS, he drives cloud data warehousing, performance optimization, and modern data engineering initiatives for enterprise clients.

Shilin Wu Principal Solution Architect @ VeloDB Shilin specializes in the design and optimization of distributed real-time analytical platforms. With a career spanning industry leaders such as Google, Ant Financial, and Confluent, Shilin brings a wealth of expertise in architecting high-performance data systems at scale, helping organizations successfully transition Apache Doris and VeloDB into production environments.