Is Convex Fundamentally Limited for Large-Scale Enterprise Data? (1M+ Records per Table)
Hi Convex community!
I'm evaluating Convex for enterprise applications and hitting what seem like fundamental scalability walls. Need honest feedback on whether I'm missing something or if Convex isn't suitable for large-scale data.
Real-World Scale:
- 50,000+ customers
- 1,000,000+ invoices
- 500,000+ products
- Users need to search across ALL this data
The Fundamental Problem:
With Convex's 16,384 document scan limit, array size limit and other limits, it seems impossible to:
1. Search invoices by customer name when popular customers have 10,000+ invoices
2. Search products by category when categories contain 50,000+ items
3. Find invoices in date ranges when busy months have 100,000+ invoices
4. Any text search that might match more than 16k documents
Critical Questions:
1. Is Convex enterprise-ready? Can it handle million-record datasets that enterprises routinely work with?
2. Search at scale: How do you implement search functionality when result sets can unpredictably exceed scan limits?
The Real Question:
Is Convex positioned as a "small-to-medium scale" solution, or am I fundamentally misunderstanding how to architect large-scale applications on the platform?
Examples I'm struggling with:
- Search 1M invoices by customer name
- Filter 500k products by multiple criteria
- Generate reports across 100k+ records
- Paginate through large unfiltered dataset
I need to know: Should I be looking at traditional databases for the heavy lifting, or is there a "Convex way" to handle enterprise-scale data that I'm missing?
This is make-or-break for platform adoption. Any honest guidance about Convex's intended scale and architectural patterns would be incredibly helpful.
I'm evaluating Convex for enterprise applications and hitting what seem like fundamental scalability walls. Need honest feedback on whether I'm missing something or if Convex isn't suitable for large-scale data.
Real-World Scale:
- 50,000+ customers
- 1,000,000+ invoices
- 500,000+ products
- Users need to search across ALL this data
The Fundamental Problem:
With Convex's 16,384 document scan limit, array size limit and other limits, it seems impossible to:
1. Search invoices by customer name when popular customers have 10,000+ invoices
2. Search products by category when categories contain 50,000+ items
3. Find invoices in date ranges when busy months have 100,000+ invoices
4. Any text search that might match more than 16k documents
Critical Questions:
1. Is Convex enterprise-ready? Can it handle million-record datasets that enterprises routinely work with?
2. Search at scale: How do you implement search functionality when result sets can unpredictably exceed scan limits?
The Real Question:
Is Convex positioned as a "small-to-medium scale" solution, or am I fundamentally misunderstanding how to architect large-scale applications on the platform?
Examples I'm struggling with:
- Search 1M invoices by customer name
- Filter 500k products by multiple criteria
- Generate reports across 100k+ records
- Paginate through large unfiltered dataset
I need to know: Should I be looking at traditional databases for the heavy lifting, or is there a "Convex way" to handle enterprise-scale data that I'm missing?
This is make-or-break for platform adoption. Any honest guidance about Convex's intended scale and architectural patterns would be incredibly helpful.
