330+ data teams share what's working (and what's not)
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Re: 330+ data teams share what's working (and what's not)
#2We at Metabase asked 338 teams in our community about how they build and use their data stacks, from tool choices to AI adoption, and built a community resource for data stack decisions in 2025.
Some of our findings: - Postgres wins it all: #1 transactional DB and #1 analytics storage - 50% of teams skip warehouses/lakes - Data teams stay small: most are just 1-3 people, even at big companies - AI trust is shaky: average confidence only 5.5/10
There’s much more to see. Check it out and let us know what you think.
Re: 330+ data teams share what's working (and what's not)
#3We at Metabase asked 338 teams in our community about how they build and use their data stacks, from tool choices to AI adoption, and built a community resource for data stack decisions in 2025. Some of our findings: - Postgres wins it all: #1 transactional DB and #1 analytics storage - 50% of teams skip warehouses/lakes - Data teams stay small: most are just 1-3 people, even at big companies - AI trust is shaky: ave…
"Just use postgres" :)
Re: 330+ data teams share what's working (and what's not)
#4This seems like valuable data, and I don’t like complaining about UX on hn but…
I’m giving up. The tab layout and scrolling are effectively unusable on my iPhone.
Re: 330+ data teams share what's working (and what's not)
#5This seems like valuable data, and I don’t like complaining about UX on hn but… I’m giving up. The tab layout and scrolling are effectively unusable on my iPhone.
UX does not seem to be a strong side of Metabase. I’ve recently started creating dashboards in Metabase, having used Grafana extensively, and it’s not very pleasant. Too bad Grafana has very limited options for not time-based visualizations.
Re: 330+ data teams share what's working (and what's not)
#6We at Metabase asked 338 teams in our community about how they build and use their data stacks, from tool choices to AI adoption, and built a community resource for data stack decisions in 2025. Some of our findings: - Postgres wins it all: #1 transactional DB and #1 analytics storage - 50% of teams skip warehouses/lakes - Data teams stay small: most are just 1-3 people, even at big companies - AI trust is shaky: ave…
I’m surprised that Clickhouse is not more prominent in OLAP tech. Such a versatile DB.
Re: 330+ data teams share what's working (and what's not)
#7if you‘re wondering where all the content is, you might have made the same mistake as me and not seen the tab bar up top!