PostgreSQL extension to scale out real-time reads and writes pg_shard is an open source sharding extension for PostgreSQL. It shards PostgreSQL tables for horizontal scale, and replicates them for high availability. The extension also seamlessly distributes SQL statements, without requiring any changes to the application layer. pg_shard addresses many NoSQL use-cases, and becomes more powerful with the new JSONB data type. Further, the extension leverages the rich analytic capabilities in PostgreSQL, and enables real-time analytics for big data sets. In this talk, we first summarize challenges in distributed systems associated with scaling out databases. We then describe "logical sharding", and discuss how it helps overcome these challenges. Next, we show how pg_shard uses hook APIs, such as the planner and executor hooks, to make PostgreSQL a powerful distributed database. We then cover example customer use-cases, and conclude with a futuristic demo: a distributed table with JSONB fields, backed by a dynamically changing row and columnar store. pg_shard is an open source sharding extension for PostgreSQL. It shards PostgreSQL tables for horizontal scale, and replicates them for high availability. The extension also seamlessly distributes SQL statements, without requiring any changes to the application layer. pg_shard addresses many NoSQL use-cases, and becomes more powerful with the new JSONB data type. Further, the extension leverages the rich analytic capabilities in PostgreSQL, and enables real-time analytics for big data sets. In this talk, we first summarize challenges in distributed systems: dynamically scaling a cluster when new machines are added or old ones fail, and distributed consistency semantics in the face of failures. We then describe "logical sharding", and show how it helps overcome these challenges. We also discuss this idea's application to Postgres. Next, we show how pg_shard uses hook APIs, such as the planner and executor hooks, to make PostgreSQL a powerful distributed database. We then cover example customer use-cases, and conclude with a futuristic demo: a distributed table with JSONB fields, backed by a dynamically changing row and columnar store.