Datadog developed a managed data replication platform to address the complexities of moving data between diverse systems, which was necessary to support the company's growth and operational needs. Initially, a shared Postgres database managed key product pages efficiently, but as data volumes increased, it faced scaling challenges, prompting Datadog to re-architect its system. They implemented a dedicated search platform, leading to significant improvements in query latencies and user experience. The platform evolved to support diverse use cases by employing asynchronous replication, utilizing technologies like Debezium and Kafka Connect, and ensuring schema compatibility to handle constant changes. Automation through Temporal workflows reduced operational overhead, enabling reliable, modular pipeline provisioning. This approach allowed Datadog to transition from a single-purpose solution to a scalable, multi-tenant platform, supporting various replication scenarios and enhancing data locality and resilience. The company emphasized flexibility and customization, empowering teams to tailor data flows to their needs using Kafka Sink Connector transformations and a custom enrichment API. Through strategic architectural decisions, Datadog achieved a robust, extensible platform while continuing to innovate in the data replication space.