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authorMartin Kagamino Lehoux <martin@lehoux.net>2026-01-29 07:34:49 +0100
committerMartin Kagamino Lehoux <martin@lehoux.net>2026-01-29 07:34:49 +0100
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----
-title: "Managing analytical workloads in startups"
-draft: true
-description: ""
-categories:
- - PostgreSQL
----
-
-## Current issues
-
-- Issues with querying large dataset in online postgres (90GB)
-- The dataset is analytics events and some business models.
-- Often used for AB testing purpose, for instance measuring conversion rates grouped by some experiment values.
-- We a have a readonly database, the queries are slow
-
-## Hypothesis/Solutions
-
-- Writing better queries: this also needs to be maintainable (e.g. we add more and more queries, it should not need to be carefully handcrafted)
-- Using another engine
- - Postgres like but OLAP oriented
- - Pure OLAP (Clockhouse, Duckdb)
- - AWS for simplicity (Athena or Redshift Spectrum)
- - Scripts on parquet files: maximum adaptability
-- How to get the data?
- - it seems that it is already parquets
- - it looks too slow to download all the data periodically: process in the cloud or incremental sync
-
-## Resources
-
-- https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_ExportSnapshot.html