Skip to content
Artwork for Project Geospatial
Project Geospatial · September 7 · 6 min

FedGeoDay 2025 | Lightning Talk - Adam Timm

Adam Timm, Field CTO at Crunchy Data, introduces Crunchy Data Warehouse, a new solution designed to merge the capabilities of data lakes and PostgreSQL databases. He highlights the traditional struggles of scaling PostgreSQL for analytical workloads and the challenges of using data lakes for operational tasks. Crunchy Data Warehouse addresses this by allowing users to query data stored directly in cloud storage (like S3) in formats such as Iceberg and Parquet, eliminating the need for complex ETL processes. It features an embedded vectorized query engine for fast analytics and supports mixing transactional and analytical workloads through a single PostgreSQL interface. The product also enables data pipeline processing and logical replication within PostgreSQL to manage Iceberg and Parquet files natively. Crucially, Crunchy Data Warehouse is built on a pure PostgreSQL approach, preserving compatibility with the full ecosystem of PostgreSQL extensions and keeping pace with community innovations, aiming to build resilient systems and integrate large open datasets like OpenStreetMap and Overture Maps efficiently. • Introduces Crunchy Data Warehouse, a new product bringing data lake capabilities into PostgreSQL. • Aims to solve the challenge of scaling PostgreSQL for analytics and warehousing and integrating it with operational workloads. • Allows querying data directly in cloud storage (like S3) in formats such as Iceberg and Parquet, removing the need for complex ETL pipelines. • Uses an embedded vectorized query engine for fast analytical queries on data stored in S3. • Supports mixing transactional and analytical workloads through a single PostgreSQL interface. • Enables data pipeline processing and logical replication within PostgreSQL for native Iceberg/Parquet management. • Takes a pure PostgreSQL approach, preserving compatibility with the full ecosystem of extensions and community innovation. • Enables the integration of large open datasets like OpenStreetMap and Overture Maps. • Aims to support the building of resilient systems and offers potential cost savings (mentioning an internal use case saving $30k/month). For more content like this check out www.projectgeospatial.com #FedGeoDay #Geospatial #OpenSource #Resilience #CrunchyData #PostgreSQL #DataWarehouse #DataLake #Iceberg #Parquet #CloudStorage #Analytics #ETL #Database #GeospatialData

0:00-6:22

transcript

No transcript — this publisher did not publish one.

show notes

Adam Timm, Field CTO at Crunchy Data, introduces Crunchy Data Warehouse, a new solution designed to merge the capabilities of data lakes and PostgreSQL databases. He highlights the traditional struggles of scaling PostgreSQL for analytical workloads and the challenges of using data lakes for operational tasks. Crunchy Data Warehouse addresses this by allowing users to query data stored directly in cloud storage (like S3) in formats such as Iceberg and Parquet, eliminating the need for complex ETL processes. It features an embedded vectorized query engine for fast analytics and supports mixing transactional and analytical workloads through a single PostgreSQL interface. The product also enables data pipeline processing and logical replication within PostgreSQL to manage Iceberg and Parquet files natively. Crucially, Crunchy Data Warehouse is built on a pure PostgreSQL approach, preserving compatibility with the full ecosystem of PostgreSQL extensions and keeping pace with community innovations, aiming to build resilient systems and integrate large open datasets like OpenStreetMap and Overture Maps efficiently.


• Introduces Crunchy Data Warehouse, a new product bringing data lake capabilities into PostgreSQL.

• Aims to solve the challenge of scaling PostgreSQL for analytics and warehousing and integrating it with operational workloads.

• Allows querying data directly in cloud storage (like S3) in formats such as Iceberg and Parquet, removing the need for complex ETL pipelines.

• Uses an embedded vectorized query engine for fast analytical queries on data stored in S3.

• Supports mixing transactional and analytical workloads through a single PostgreSQL interface.

• Enables data pipeline processing and logical replication within PostgreSQL for native Iceberg/Parquet management.

• Takes a pure PostgreSQL approach, preserving compatibility with the full ecosystem of extensions and community innovation.

• Enables the integration of large open datasets like OpenStreetMap and Overture Maps.

• Aims to support the building of resilient systems and offers potential cost savings (mentioning an internal use case saving $30k/month).


For more content like this check out www.projectgeospatial.com


#FedGeoDay #Geospatial #OpenSource #Resilience #CrunchyData #PostgreSQL #DataWarehouse #DataLake #Iceberg #Parquet #CloudStorage #Analytics #ETL #Database #GeospatialData