I’m looking for suggestions on database platforms that can handle massive datasets with over 200k entries. Currently using Google Sheets and Airtable but running into major performance issues when the data gets this large. The response times become really slow and Google’s API has some annoying restrictions that cause problems. Need something that works smoothly with n8n workflows and doesn’t require a PhD in database management to figure out. Speed is crucial since I’m dealing with lead data that needs quick access and updates. What alternatives have you guys tried that actually work well at this scale?
postgres is a great choice! way more efficient than sheets. i got it working with n8n, super easy integration, handling 300k records with no lag. give it a shot!
Switched from Airtable to MongoDB 8 months back when I hit the same scaling wall around 180k records. Night and day difference - complex queries that took 30+ seconds now run in under 2 seconds. MongoDB Atlas is pretty straightforward to set up, and their free tier handles a lot before you need to pay. The n8n MongoDB node works great once you nail the connection string setup. Pro tip: index your most-queried fields right away or you’ll still have performance issues even with a proper database. For leads, I indexed timestamp and status fields - massive improvement in workflow speed.
Hit the same wall at 250k records last year. Switched to MySQL and it fixed everything.
The n8n MySQL node works great - rarely causes issues. What really helped was setting up proper primary keys and writing queries that actually use them. Most people screw this up then wonder why their database crawls.
For leads, I keep hot data (recent leads, active prospects) in one table and archive old stuff quarterly. Keeps main queries fast since you’re not scanning months of dead leads.
MySQL hosting’s cheap too. I pay $15/month for managed hosting that handles 500k+ records easily. Beats fighting Google Sheets rate limits or paying Airtable’s crazy scaling costs.
Just set up foreign keys right if you split data across tables. Saves major headaches later.