SaaS ideas your next customers are already looking for
100 SaaS startup ideas for the people who said they'd pay, from agency owners to dentists. Micro SaaS ideas, AI SaaS ideas and B2B SaaS ideas: find yours, build it, sign them up.
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Pain points in business: what people struggle with
Search the problems to solve, as people described them on Reddit and other platforms, in their own words.
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Database Schema Drift
Database schemas silently drift from code, migrations, and across environments, causing runtime errors, broken pipelines, and data loss.
In their words
Every AI tool I've tried will happily add a required non-nullable column to a populated table with no default value.
the best way to allow people to collaborate on evolving event schemas for future versions and being able to share these with other teams
the painful ones for us were when the job still went green but the number on the dash was wrong
AI creates the tables but never comes back to add indexes based on how you actually query.
features would not get released because no one knew how to avoid or handle the large merge conflicts
our qa test isn't actually testing what it should because we're manually editing files before each environment deployment
Inherited a schema where roughly half the columns are self-explanatory and the rest are things like flag_3 and val_b.
Constant production incidents, and none of the managers want to consider slowing down so we can pull of some migrations without everything in flux.
if you get that MySQL 8.0 EOL email, upgrade as soon as possible or prepare yourself for a surprise in your bill
This will run for 5+ minutes just to compare this small database. Large databases can take over 15 minutes to compare. There is no indication of how much progress has been made
we have are facing a blocker in this migration since our codebase is heavy dependent on the stream feature of dynamodb
about 20% of the time, the migration fails in some unexpected way
the amount of grunt programming and testing and repetitive work is just not great
New feature development was a huge PITA as was changing schema in any way.
developers and data engineers
Where they talk
- r/databricks
- r/dataengineering
- r/AI_Agents
- r/MicrosoftFabric
- r/Supabase
- r/SQL
- r/postgres
- r/SQLServer
Tools they use today
- dbt
- Databricks
- PostgreSQL
- Supabase
- git
- Microsoft Fabric
- Claude
- Claude Code
Why those fall short
- sprocs released to DB, app no longer in control; rollbacks painful
- AI does not know query patterns or production scale
- no strategy, cache invalidation too complex, schema never hits sweet spot
- Comments rot, nobody reads them, no way to know if still true
- auto column mapping fails when files differ; no upstream change notification
Map of ideas
Drawing the map…