Postgres engines can now connect to large data repositories using extensions like pg_lake, allowing access to files in object storage formats such as CSV, JSON, Apache Parquet™, and Apache Iceberg™. The Apache AGE™ extension enhances data usability through graph relationships, enabling complex queries that require both graph traversal and analytical aggregation. Apache AGE introduces openCypher graph query support within Postgres, allowing for integration without data movement, as both Iceberg tables and graphs reside in the same database. This integration facilitates the construction of graphs from lake tables, allows for combining SQL and Cypher queries, and simplifies operational processes by consolidating application connection, security, and backups into a single workflow. An example of this integration is a healthcare platform using Iceberg tables on Amazon S3, which includes various data types such as claims, providers, patients, and referrals. To utilize these features, necessary Postgres extensions must be loaded, with pg_lake operating alongside a sidecar, the pgduck_server, for Iceberg operations.