Ippokratis Pandis

Teams want to run analytics on fresh transactional data without building fragile ETL pipelines or maintaining fleets of read replicas. Lakebase addresses this by separating Postgres storage from compute. In this session, you'll see how the lakebase architecture takes this one step further, for powering low-latency operational analytics for use cases including fraud detection, real-time dashboards, all without duplicating data or slowing down production systems.

Exponential data growth has created unique challenges for data practitioners to manage data warehouses that can support high performance workloads at scale within cost constraints.

Amazon Redshift is continuously reinventing data warehousing to provide powerful analytics in the cloud for you. Amazon Redshift supports your needs for high-performance execution with complex, analytical queries with high concurrency and deep integrations with other AWS services, performing rich analytics on all data and ML-based autonomics that make analytics easier.

Getting timely value from data requires high-performance systems that can deliver performance at any scale while keeping costs low. Amazon Redshift, the fastest, easiest, and most widely used cloud data warehouse, empowers tens of thousands of organizations to analyze exabytes of data every day.

Amazon Redshift provides multiple features to help you deliver consistent performance, even as workloads grow and vary. Learn how to use concurrency scaling, data sharing, and more on their own and together to manage your workloads.

Every organization struggles with dark data--data that is not being analyzed due to the complexity, scalability, performance, or cost issues of loading the data into their data warehouse. Amazon Redshift eliminates the dark data problem by giving you the freedom to store data where you want, in the format you want, and have it available for analytics when you need it.

This session dives deep into the capabilities of Amazon Redshift. See how Amazon Redshift achieves its state-of-the-art performance and learn about all aspects of elasticity, from the compute and data elasticity within a single cluster to elasticity across multiple clusters.