Stop managing multiple databases. Postgres extensions replace Elasticsearch, Pinecone, Redis, MongoDB, and InfluxDB with BM25, vectors, JSONB, and time-series in one database.

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Postgres extensions can replace specialized databases like Elasticsearch, Pinecone, Redis, MongoDB, and InfluxDB using the same core algorithms (BM25, HNSW, DiskANN). Managing one database instead of seven reduces operational complexity, eliminates data sync issues, simplifies AI agent testing, and cuts infrastructure overhead. Extensions like pg_textsearch, pgvector, pgvectorscale, TimescaleDB, and PostGIS provide full-text search, vector search, time-series, caching, document storage, and geospatial capabilities within Postgres. For 99% of companies, Postgres handles all database needs without the cognitive load, monitoring burden, and failure modes of database sprawl.

It’s 2026, Just Use Postgres

“But Specialized Databases Are Better!”

As a natural lazy person, I approve this message lmao. I would rather just get really good with one database like postgres than juggle a bunch.

Completely agree with this approach. Start with PostgreSQL, and only when you hit specific bottlenecks should you consider moving certain workloads to more specialized databases. In my experience, 90% of the time you won’t need anything beyond Postgres. it’s remarkably capable for a wide range of use cases. And for that remaining 10%, you’ll have clear, well-defined requirements by then, which actually makes choosing and implementing the right specialized solution much easier.

I used to think that I need to learn many new things to be productive. It seems to be counter productive. Totally agree with this. I’ll give it a try now!

Taking “it’s the current year” as an argument against the author, it’s pure reddit-tier logic. Decided to go full sqlitemaxx because of this. Extreme local aura, absolute portability chad, and setuptimemaxxing like crazy. Mogging all these bloated alternatives into the ground.

Timescale db is one of the best tool that a developer can use when building applications that needs a large amount of time series-data. Of course on large deployements it needs to be assisted with optimization or other tools. With timescale I built LogTide a log management system and we store without problems around 300m logs