Marco Slot
@marcoslot.com
Mostly posts about PostgreSQL, Snowflake Postgres, and PostgreSQL extensions.
Formerly Crunchy Data, Microsoft, Citus Data, AWS, TCD, VU
Formerly Crunchy Data, Microsoft, Citus Data, AWS, TCD, VU
Generative AI comes up with details that would be hilarious, if it wasn't so mind boggling that it can come up with these details.
May 4, 2025 at 9:33 PM
Generative AI comes up with details that would be hilarious, if it wasn't so mind boggling that it can come up with these details.
And there it is: Native logical replication from any Postgres server to Iceberg managed by Crunchy Data Warehouse.
Speed up Postgres analytical queries 100x with 2 commands.
Speed up Postgres analytical queries 100x with 2 commands.
April 22, 2025 at 2:48 PM
And there it is: Native logical replication from any Postgres server to Iceberg managed by Crunchy Data Warehouse.
Speed up Postgres analytical queries 100x with 2 commands.
Speed up Postgres analytical queries 100x with 2 commands.
Postgres is increasingly becoming a versatile data platform, instead of just an operational database.
Using pg_parquet you can trivially export data to S3, and using Crunchy Data Warehouse you can just as easily query or import Parquet files from PostgreSQL.
Using pg_parquet you can trivially export data to S3, and using Crunchy Data Warehouse you can just as easily query or import Parquet files from PostgreSQL.
February 7, 2025 at 11:11 AM
Postgres is increasingly becoming a versatile data platform, instead of just an operational database.
Using pg_parquet you can trivially export data to S3, and using Crunchy Data Warehouse you can just as easily query or import Parquet files from PostgreSQL.
Using pg_parquet you can trivially export data to S3, and using Crunchy Data Warehouse you can just as easily query or import Parquet files from PostgreSQL.
End-to-end demo of the new pg_incremental extension.
There's raw events table and a summary table containing view counts.
You then define a pipeline using an insert..select command, and keeps running that to do fast, reliable, incremental processing in the background.
There's raw events table and a summary table containing view counts.
You then define a pipeline using an insert..select command, and keeps running that to do fast, reliable, incremental processing in the background.
December 17, 2024 at 5:35 PM
End-to-end demo of the new pg_incremental extension.
There's raw events table and a summary table containing view counts.
You then define a pipeline using an insert..select command, and keeps running that to do fast, reliable, incremental processing in the background.
There's raw events table and a summary table containing view counts.
You then define a pipeline using an insert..select command, and keeps running that to do fast, reliable, incremental processing in the background.
It's also not so easy to get started right now, with only Spark supporting the catalog and no way to create tables without a query engine. Presumably that will improve quickly.
Still, I think this is what getting started with Iceberg should look like:
Still, I think this is what getting started with Iceberg should look like:
December 4, 2024 at 10:21 PM
It's also not so easy to get started right now, with only Spark supporting the catalog and no way to create tables without a query engine. Presumably that will improve quickly.
Still, I think this is what getting started with Iceberg should look like:
Still, I think this is what getting started with Iceberg should look like:
November 22, 2024 at 1:30 PM
The performance difference between Iceberg and heap tables for analytical operations in Crunchy Data Warehouse can be pretty big.
But you really start noticing the difference when you run through several steps.
But you really start noticing the difference when you run through several steps.
November 20, 2024 at 9:31 PM
The performance difference between Iceberg and heap tables for analytical operations in Crunchy Data Warehouse can be pretty big.
But you really start noticing the difference when you run through several steps.
But you really start noticing the difference when you run through several steps.
Quick demo of Iceberg in PostgreSQL with Crunchy Data Warehouse.
Create an Iceberg table from a file, load some more data, and run fast queries.
Create an Iceberg table from a file, load some more data, and run fast queries.
November 20, 2024 at 5:32 PM
Quick demo of Iceberg in PostgreSQL with Crunchy Data Warehouse.
Create an Iceberg table from a file, load some more data, and run fast queries.
Create an Iceberg table from a file, load some more data, and run fast queries.