Compare / Pinecone
WarpSearch vs Pinecone
Serverless vector database. Each query is billed by the size of the namespace it searches: 1 read unit per GB.
How they bill
| WarpSearch | Pinecone | |
|---|---|---|
| Billing unit | Flat $2 per million requests | $16 to $18 per million read units; 1 read unit per GB of namespace per query |
| Storage | $0.08 per GB-month, lower at volume | $0.33 per GB-month |
| Writes | $1.00 per GB | $4 to $4.50 per million write units (1 per KB); replacing a record also bills the old one |
| Minimum | $10 a month | $50 a month (Standard) |
| Keyword search | BM25 with Elasticsearch query syntax | Full-text search on document indexes; hybrid via client-side fusion or sparse vectors |
| Aggregations and facets | Yes | No |
Price
Monthly cost for four common workloads, at list prices in US East.
1M text chunks with 768-dim embeddings, 7 GB of JSON. 1M queries a month spread through the day. 1 GB written a month.
| WarpSearch | Pinecone | |
|---|---|---|
| Storage | $0.56 (7 GB held x $0.08) | $2.31 |
| Writes | $1.00 (1 GB x $1.00) | $4 to $9 |
| Search | $2.00 (1M requests) | $112 to $126 (7 read units per query) |
| Data returned | $0 (about 40 GB, inside the free 100 GB) | $0 (inside 100 GB) |
| Minimum | $10 minimum applies (usage is $3.56) | $50, cleared |
| Total a month | $10 | $118 to $137 |
5M products with 384-dim embeddings, 10 GB of JSON. 50M queries a month (about 19 a second on average). 20 GB written a month.
| WarpSearch | Pinecone | |
|---|---|---|
| Storage | $0.60 (7.5 GB held x $0.08) | $3.30 |
| Writes | $20 (20 GB x $1.00) | $80 to $160 |
| Search | $100 (50M requests) | $8,000 to $9,000 (10 read units per query) |
| Data returned | $18 (250 GB returned, 100 GB free, before compression) | $15 |
| Minimum | Cleared | Cleared |
| Total a month | $139 | $8,100 to $9,200 |
Dedicated Read Nodes ($336 per node-month) could bring this to about $435 to $1,525. Node capacity is not published.
10 TB of raw logs kept searchable. 1 TB written a month. 10,000 dashboard aggregation queries a month.
| WarpSearch | Pinecone | |
|---|---|---|
| Total a month | $1,465 | Not a fit |
No aggregations.
1 PB of raw logs kept searchable. 50 TB written a month. 100,000 heavy aggregation queries a month.
| WarpSearch | Pinecone | |
|---|---|---|
| Total a month | $39,060 | Not a fit |
No aggregations.
Performance
What Pinecone publishes
| On-demand query latency | Not published |
|---|---|
| Dedicated Read Nodes, 135M vectors | 600 queries/s at 45 ms median, 96 ms p99 (customer story) |
| Recall, 2.68M x 1536-dim | 84% to 96%, depending on scan_factor |
| Time to searchable | Eventually consistent, "a few seconds", no SLA |
Pinecone does not publish latency for its on-demand tier. Its published numbers are customer stories on Dedicated Read Nodes at 100M+ vectors, which we have not tested at. At 1 to 10M vectors we measure 6 to 16 ms median at 0.95+ recall on most datasets.
What we measured
| Test | Result |
|---|---|
| Keyword search, 2.8M docs (LoTTE) | 2.1 ms median, 3,700 queries/s |
| Keyword search, 10M passages (MS MARCO v2) | 2.4 ms median (5.4 ms with an exact total hit count) |
| Keyword search, small BEIR sets | 1 to 6 ms median |
| Vector search, 10M x 128-dim (BigANN SIFT) | 0.964 recall@10 at 6.2 ms median, 162 queries/s |
| Vector search, 1M x 1536-dim (arXiv) | 0.961 recall@10 at 15.7 ms median |
| Filtered vector search, 10M (YFCC) | 0.959 recall@10 at 10.4 ms median |
| Log filters, 22M events (http_logs) | 1 to 2 ms median |
| Log aggregations, 22M events | 190 to 430 ms median (sort, daily histogram, avg by status) |
| Ingest, short text | 63,000 to 97,000 docs/s |
| Ingest, logs (247M events) | 76,000 to 81,000 events/s |
| Ingest, 768 to 1536-dim vectors | 2,200 to 4,000 vectors/s |
| Time to searchable | Seconds, or immediate with commit=true |
| Cold start | Not measured yet. First query on a 2.3 GB index: 17 to 19 ms vs 2.7 ms warm (page cache only) |
Measured October 2026 through our Elasticsearch-compatible API, warm cache, client in the same region, single runs. Every test ran on deliberately minimal hardware, 2 to 4 CPUs (a 4 CPU container or an AWS i8g.large with 2 vCPUs), so these are the least favorable results we can produce. More hardware only improves them. Numbers exclude internet round trips.
Bottom line
Choose WarpSearch for
- Price at query volume: our requests cost the same at any index size. Pinecone's cost grows with every GB you search.
- RAG: $10 vs about $120. Catalog: $139 vs about $8,100 on demand.
- Keyword, vector, filters and facets in one index, with Elasticsearch-compatible queries.
Choose Pinecone for
- Proven scale: Pinecone publishes results at over a billion vectors.
- Vector recall: on some embedding sets ours is still below 0.95.
For RAG and product search, WarpSearch is 10x to 60x cheaper than Pinecone on demand and adds full keyword search and facets. Pinecone is the proven choice at billion-vector scale.
Sources
Read and write unit rates vary by region; the range covers Standard plan regions. Text stored with each record counts toward namespace size, so it raises the cost of every query. Prices checked October 20, 2026. List prices in US dollars, before discounts. Estimates are marked. Tell us if something is out of date: contact us.