DuckDB

“You can use it to connect every single data source that's around your company and then use it as a federation engine”

“Being able to put it behind an HTTP service / load balancer and implement horizontal scaling based on resource utilization”

“I swapped out some data analytics processing that was originally implemented with Python & Postgres to DuckDB and have been immensely pleased with the outcome.”

“their new c++ extension api is also gonna be faster from the perspective of development / distribution of those extensions”

“it's definitely an amazing piece of technology, but it didn't provide the full "database" experience we needed”

“The mental model of describing a series of reproducible transformations on normalized tables is more intuitive to me.”

“I was a real fan from the very beginning, but now DuckDB 2.0 "as a server" and 5. asynchronous I/O looks aimed at something very different from what I thought first.”

“It is a game changer for me for the "local analytics" space, and its ability to scale up to a large degree helps a lot.”

“Duckdb has concurrency limits so you can't have a writer and a reader on the same file if they're not the same process”

“you can query pandas/polars/arrow tables directly w/ duckdb and use whatever stats packages you feel like alongside it”

“the duckdb csv parser is the fastest I could find and helped save a data project with hundreds of gigabytes of csv pain”

“In the last two years, DuckDB improved a lot. Importantly, the C interface now provides a batched system for both inserts and querying”

“I think DuckDB is simply amazing and truly an amazing piece of technology for anyone working with large amounts of data.”

“It's just so much easier to write sql against csv/json/whatever format data in jupyter/marimo notebooks through duckdb rather than reasoning through pandas.”

“DuckDB is amazing for any sort of fast data analysis when the data is small enough that it can fit on your laptop”

“DuckDB has been probably my most used tool in 2026 - if you're comfortable with SQL it's incredible at quickly prototyping and slicing / dicing data.”

“DuckDB is 5x-10x better than SQLite and orders of magnitude simpler/faster than spinning up a dedicated Postgres database.”

“DuckDB will (extremely efficiently) scan the whole table and will blow many other tools out of the water while doing so”

“Ecosystem is still surprisingly quite young and I end up discovering bugs not made it into official releases yet”

“I'd be lost without it for log analysis. It's like a swiss army knife for making sense of disparate or large sets of data.”

“There's something fundamentally wrong with the codebase/architecture if there's so many memory problems.”

“Ingest rates were tough. We partitioned and ran over multiple duckdb instances too (and wrangled the complexity).”

“I have a deep appreciation for DuckDB, but I am afraid the confluence of brilliant ideas makes it ever more complicated to adopt”

“DuckDB can operate well on a wide range of infrastructure and is well suited for operating in resource constrained environments”

“impressive that DuckDB managed SF300 with only 8GB RAM, even if query 67 taking 51 minutes is a red flag”

“the ability to do deep investigations on the data as you're designing the pipeline (or when things go wrong) is very useful”

“the availability of DuckDB and fast multi core machines with even faster SSDs makes the need for distribution all the more niche”

“Things like foreign keys, expressions that span multiple tables effortlessly, normalization, check constraints, unique constraints, and primary keys work perfectly right off the shelf.”

“Their csv support coupled with lots of functions and fast & easy iterative data discovery has totally changed how I approach investigation problems.”

“It's so much easier to think in terms of knew machine that gets it's resources used efficiently instead of distributed/cloud processes.”

“We use it in browser and on server at Count to make data warehouses more responsive for multiuser and agentic work.”

“DuckDB can't get enough love! Beyond being a really performant database, being so friendly is really underrated”

“I use DuckDB for nearly everything data related because it's simply the most scalable format/tool/lib from a handful of rows to billions.”

“makes working with random JSON much nicer than SQLite, not least because I can extract JSON fields to dense columnar representations”

“DuckDB's reasonable syntax, fast vectorized everything, and support for ingesting the hairiest of data as in-DB ETL”

“It also still has some quirks and foot-guns that need moderately knowledgeable systems people to operate”

“this is still too slow for quick inserts, because duckdb (like all columnar stores) is designed for batches”

“Single file per database, Multiple ingestion formats, full text search, S3 support, Parquet file support, columnar storage.”

“Each row group stores metadata about the set it contains that can be used to prune out data that doesn't need to be scanned”

“it's very cool having a local instance of something akin to snowflake when it comes to processing and aggregating on Big Data”