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Posts about Crunchy Data Warehouse

  • Postgres Materialized Views from Parquet in S3 with Zero ETL

    Marco Slot

    Data pipelines for IoT applications often involve multiple different systems. First, raw data is gathered in object storage, then several transformations happen in analytics systems, and finally results are written into transactional databases to be accessed by low latency dashboards. While a lot of interesting engineering goes into these systems, things are much simpler if you can do everything in Postgres. Crunchy Bridge for Analytics is a managed PostgreSQL offering that integrates DuckDB...

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  • Postgres Powered by DuckDB: The Modern Data Stack in a Box

    Marco Slot

    Postgres for analytics has always been a huge question mark. By using PostgreSQL's extension APIs, integrating DuckDB as a query engine for state-of-the-art analytics performance without forking either project could Postgres be the analytics database too? Bringing an analytical query engine into a transactional database system raises many interesting possibilities and questions. In this blog post I want to reflect on what makes these workloads and system architectures so different and what br...

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  • Query Hugging Face Datasets from Postgres

    Elizabeth Christensen

    If you missed the database news lately, you could have missed that we just fused DuckDB with Postgres to build a really fast analytics platform based on Postgres. There’s so many interesting things you can do with this platform so expect to hear from me again 😉. Today I just want to show off one really simple trick for getting big data sets or training data into Postgres through Hugging Face. Hugging Face is a community repository of datasets, LLMs, models and other resources for Machine L...

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  • Running TPC-H Queries on Iceberg Tables from PostgreSQL

    Önder Kalacı

    We recently introduced support for querying Iceberg tables from PostgreSQL in Crunchy Bridge for Analytics. Iceberg defines a way to store tables in data lakes (usually as Parquet files in S3) with support for snapshots and other important database features, and it is designed with high performance analytics in mind. If you’re new to Crunchy Bridge, it offers a fully managed PostgreSQL experience. Crunchy Bridge for Analytics extends these capabilities, enabling you to query and interact wit...

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  • Crunchy Bridge Adds Iceberg to Postgres & Powerful Analytics Features

    Marco Slot

    In April we launched Crunchy Bridge for Analytics , which is a managed PostgreSQL option that enables fast and seamless querying of your data lake. Our initial release was focused on building a rock solid foundation for high performance analytics in PostgreSQL. We have since been hard at work turning it into a comprehensive analytics solution. Our goals in building Crunchy Bridge for Analytics are to: • Make it very easy to query data files (incl. Parquet/CSV/JSON/Iceberg) in object stores like...

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  • How We Fused DuckDB into Postgres with Crunchy Bridge for Analytics

    Marco Slot

    Last month we launched Crunchy Bridge for Analytics , a new managed PostgreSQL offering that lets you query your data lake directly from PostgreSQL. Since then, we have had quite a few exciting conversations with customers handling large amounts of data in PostgreSQL. A common question is of course: How does it work? In this post, I wanted to shed some light on the internals. Crunchy Bridge for Analytics abstracts the query engine to offer fast analytics on data in Amazon S3 in PostgreSQL. In p...

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