Introducing Crunchy Data Warehouse: A next-generation Postgres-native data warehouse. Crunchy Data Warehouse Learn more
Christopher Winslett
Christopher Winslett
You followed all the best practices, your sales dates are stored in perfect timestamp format …. but now you need to get reports by day, week, quarters, and months. You need to bin, bucket, and roll up sales data in easy to view reports. Do you need a BI tool? Not yet actually. Your Postgres database has hundreds of functions that let you query data analytics by date. By using some good old fashioned SQL - you have powerful analysis and business intelligence with date details on any data set. In...
Read MoreCraig Kerstiens
Craig Kerstiens
Today, we’re excited to release pg_parquet - an open source Postgres extension for working with Parquet files. The extension reads and writes parquet files to local disk or to S3 natively from Postgres. With pg_parquet you're able to: • Export tables or queries from Postgres to Parquet files • Ingest data from Parquet files to Postgres • Inspect the schema and metadata of existing Parquet files Export tables or queries from Postgres to Parquet files Ingest data from Parquet files to Postgres I...
Read MoreElizabeth Christensen
SQL makes sense when it's working on a single row, or even when it's aggregating across multiple rows. But what happens when you want to compare between rows of something you've already calculated? Or make groups of data and query those? Enter window functions. Window functions tend to confuse people - but they’re a pretty awesome tool in SQL for data analytics. The best part is that you don’t need charts, fancy BI tools or AI to get some actionable and useful data for your stakeholders. Window...
Read MoreMarco Slot
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...
Read MoreElizabeth Christensen
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...
Read MoreMarco Slot
Marco Slot
One of the unique characteristics of the recently launched Crunchy Bridge for Analytics is that it is effectively a hybrid between a transactional and an analytical database system. That is a powerful tool when dealing with data-intensive applications which may for example require a combination of low latency, high throughput insertion, efficient lookup of recent data, and fast interactive analytics over historical data. A common source of large data volumes is append-mostly time series data o...
Read MoreMarco Slot
Marco Slot
A lot of the world’s data lives in data lakes, huge collections of data files in object stores like Amazon S3. There are many tools for querying data lakes, but none are as versatile and have as wide an ecosystem as PostgreSQL. So, what if you could use PostgreSQL to easily query your data lake with state-of-the-art analytics performance? Today we’re announcing Crunchy Bridge for Analytics , a new offering in Crunchy Bridge that lets you query and interact with your data lake using PostgreSQL c...
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