Hey everyone, I've been doing some cost analysis for a new observability side project that needs semantic search over logs, and I keep running into the same wall: Pinecone's pricing feels surprisingly steep for a moderately-sized vector store. I'm prototyping with about 500k embeddings (1536-dimensions from `text-embedding-3-small`), and the projected monthly cost gave me pause.
Let's break down the numbers. If I go with their `s1.x1` pod (which is often the starting point for decent performance), that's $70/month fixed. The real kicker is the per-1k-vector read cost. My use case involves a fair number of queries—let's say 5,000 queries per day, with each query retrieving 10 nearest neighbors (so 50k vector reads/day). That's:
- **Storage:** 500k vectors ≈ $70 (base pod cost)
- **Reads:** (5,000 queries * 10 reads) * 30 days = 1.5M reads/month.
- At $0.036 per 1k reads (for the `s1` tier), that's **another $54/month**.
So we're looking at roughly **$124/month** just for the vector database, before even considering the embedding API costs and compute. For a side project or even a medium-complexity feature in a larger app, that starts to feel heavy.
**So what does this mean for my current stack?** My DevOps instincts tell me to evaluate alternatives, especially open-source ones I can run on my own k8s cluster. Here's a quick comparison I ran:
```yaml
# A quick docker-compose for a self-hosted option like Qdrant
version: '3.8'
services:
qdrant:
image: qdrant/qdrant
ports:
- "6333:6333"
volumes:
- ./qdrant_storage:/qdrant/storage
# Resource limits for ~500k vectors
deploy:
resources:
limits:
memory: 2G
cpus: '1'
```
Running this on a preemptible cloud VM or even on-prem could drop the cost to maybe $10-$20/month in pure infrastructure. The trade-off, of course, is operational overhead: I'm now responsible for backups, updates, and scaling.
Has anyone else done this calculus for a production-ish workload? I love Pinecone's managed simplicity and performance, but for 500k vectors where I control the query patterns, the cost/benefit seems to tilt towards self-managing. Are there other managed services (e.g., Weaviate Cloud, pgvector on Supabase) that offer a better price point at this scale without sacrificing too much on latency?
I'd love to see some real-world benchmarks on total cost of ownership, including devops hours, for a ~500k scale. Maybe the managed service is worth it if it saves me 3 hours of maintenance a month? What's your experience?
— francesc
— francesc
Have you looked at the total cost of self hosting something like pgvector on a small VPS? The pod fee alone seems high for your storage size.
I'm also curious about how they calculate reads. Is it truly per vector retrieved, or per query operation? I've seen other services meter it differently.
Great point about self hosting. I haven't tried pgvector myself, but even a cheap VPS could be way less than $70/month for storage, you're right.
> Is it truly per vector retrieved, or per query operation?
I'd like to know this too! Their pricing page says "per 1k vectors read," but I'm not sure if a query for 10 neighbors counts as 10 reads or just 1 operation. Could make a huge difference.
Has anyone here actually set up pgvector for a similar scale? I'm curious about the operational overhead.
For that scale, pgvector on a $10-15 VPS has been totally fine for me. The overhead isn't bad once it's set up.
> if a query for 10 neighbors counts as 10 reads or just 1 operation
In my experience with Pinecone, it's per vector retrieved, so 10 neighbors = 10 reads. That's where the cost can spike.
The trade-off is you're now managing backups, updates, and scaling yourself. For a side project, that's often worth it.
data over opinions
Their documentation is clear on this. It's per vector retrieved from the index during the query. So a search for 10 nearest neighbors is 10 reads. You can verify this in your usage metrics.
For your 500k scale, the operational overhead of pgvector is trivial. The real question is your tolerance for downtime. That $10 VPS has no SLA. If your side project goes down for six hours, is that acceptable? Pinecone's cost is partly for their guarantee.
If it is acceptable, then pgvector is the obvious choice. Just schedule your backups.
SLA is not a suggestion.