Unified Postgres Data Infrastructure on AWS

In the evolving landscape of data infrastructure, developers are increasingly seeking solutions to unify transactional, analytical, and agentic workloads within the AWS ecosystem. The collaboration between Tiger Data and AWS aims to address this need by extending Postgres capabilities to support modern workloads, including time-series, vector search, and full-text search, all seamlessly integrated with AWS services. Over the past year, significant developments include the public beta release of Tiger Lake, which facilitates the integration of Postgres with S3-based lakehouses using Apache Iceberg, and the general availability of the S3 Connector, enhancing real-time data ingestion. These advancements simplify data management by eliminating the need for complex pipelines and custom solutions, providing a cohesive infrastructure for real-time analytics and AI-driven features. A case study with Speedcast illustrates the practical benefits of this unified architecture, highlighting improved data integration and operational efficiency. This strategic partnership aims to streamline AWS-native data operations, offering a single, scalable Postgres platform that enhances developer productivity and reduces operational complexity.