Vector databases · November 2026 Edition
pgvector vs Pinecone
Five of fourteen models named pgvector first on the direct prompt; five named Pinecone. Both were named by all fourteen models and pgvector carries 73 labels and Pinecone 65, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
First-choice share34%21%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate8%23%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 11; printed, not drawn.
Labels7365A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, pgvector reading right to left. Rank and label count are printed, not drawn.Qdrant was named alongside these two in fourteen of the fourteen direct answers. Qdrant vs pgvector · Qdrant vs Pinecone · pgvector vs Weaviate
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the vector databases page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
pgvectorFirst choices, of fourteen modelsPinecone
Direct55
Paraphrase261 against Pinecone
Comparative05
Budget-constrained1106 against Pinecone
Scale-constrained111 against Pinecone
Negative206 against pgvector · 7 against Pinecone
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Across every category in the November 2026 Edition, pgvector and Pinecone were named in the same answer 171 times, of the 192 answers naming pgvector and the 219 naming Pinecone. In those answers Pinecone took the first choice forty-four times and pgvector forty-eight.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where pgvector and Pinecone stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | | | |
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | | | |
| Grok 4.20 | | | | | | |
| Mistral Small | | | | |||
| DeepSeek V4 Flash | | | | | | |
| Llama 4 Maverick | | | | | ||
| Qwen 3.7 Flash | | | | | | |
| Kimi K2 | | | | | | |
| GLM 4.7 FlashX | | | | | | |
| MiniMax M2.5 | | | | | | |
| GPT-6 Luna | | | | | | |
| Muse Glimmer 30B | | | | | | |
pgvector Pinecone first choice named as an alternative argued againstblank: not namedEach cell is one answer, pgvector on the left and Pinecone on the right.The direct prompt
The plain question, one answer per model, grouped by where pgvector and Pinecone stood in it.
Both were the first choice
1 of 14 modelsThe answer named them together, and the judge labeled each a first choice.Muse Glimmer 30BPinecone, pgvector alternatives: Milvus, Qdrant, Weaviate
pgvector first, Pinecone an alternative
4 of 14 modelsPinecone was named in the answer but not as the choice, or not at all.Perplexity Sonarpgvector alternatives: Pinecone, Qdrant
DeepSeek V4 Flashpgvector alternatives: Pinecone, Qdrant
Qwen 3.7 Flashpgvector alternatives: Pinecone, Qdrant
Kimi K2pgvector alternatives: Pinecone, Qdrant
Pinecone first, pgvector an alternative
4 of 14 modelspgvector was named in the answer but not as the choice, or not at all.GPT-5.4 miniPinecone alternatives: Qdrant, Weaviate, pgvector
Gemini 3.5 FlashPinecone, Qdrant alternatives: Weaviate, pgvector
Mistral SmallPinecone alternatives: Qdrant, Weaviate, pgvector
GLM 4.7 FlashXPinecone alternatives: Milvus, Qdrant, Weaviate
Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5Qdrant alternatives: MongoDB Atlas Vector Search, Pinecone, Weaviate, pgvector
Grok 4.20Qdrant alternatives: Pinecone, Weaviate, pgvector
Llama 4 MaverickQdrant alternatives: Pinecone, Weaviate, pgvector
MiniMax M2.5Qdrant, Weaviate alternatives: Milvus, Pinecone, pgvector
GPT-6 LunaQdrant alternatives: Pinecone, pgvector
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
pgvector leads by sixteen points.
pgvector35%#1 of 9Pinecone19%#3 of 9Mid-marketThe figures above
pgvector leads by thirteen points.
pgvector34%#2 of 11Pinecone21%#3 of 11Enterprise
The order flips: Pinecone leads at enterprise.
Pinecone45%#1 of 13pgvector7%#4 of 13What the models said about pgvector
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“pgvector does not natively support GPU acceleration or disk-optimized indexes, and at billion-scale workloads typically require more advanced sharding strategies” Claude Haiku 4.5 · negative prompt · soft negative
“Using vectors beside your application data in Postgres via pgvector is often the safest default until measured retrieval requirements force a dedicated engine.” Muse Glimmer 30B · negative prompt · soft negative
“pgvector for large, high-throughput workloads with selective filters or many tenants... approximate-index filtering can return too few results” GPT-6 Luna · negative prompt · soft negative
“the recommendation is to start with pgvector unless your scale, query patterns, or operational constraints provide specific evidence otherwise” Claude Haiku 4.5 · scale prompt · first choice
“Start simple: Use pgvector (in Postgres) or SQLite with vector extensions for most apps—it's battle-tested, avoids new tech debt” Grok 4.20 · negative prompt · first choice
“If your company already uses PostgreSQL for standard application data, pgvector is almost always the most cost-effective choice.” Gemini 3.5 Flash · budget prompt · first choice
What the models said about Pinecone
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid for a limited budget: Pinecone — managed services with $50 minimums and costs that blow past initial estimates” DeepSeek V4 Flash · budget prompt · hard negative
“What to Avoid on a Tight Budget - Managed services like Pinecone (starts at ~$70/month for basics” Grok 4.20 · budget prompt · hard negative
“What to Avoid on a Budget - Pinecone — Excellent product but starts at ~$70/month” MiniMax M2.5 · budget prompt · hard negative
“The most widely adopted vector database in the mid-market, with a 57% adoption rate... If you want the most popular and easiest managed solution, choose Pinecone.” Mistral Small · direct prompt · first choice
“### 1. Pinecone (Best for Simplicity) ... Choose Pinecone if you prioritize operational simplicity and have modest data volumes” Claude Haiku 4.5 · paraphrase prompt · first choice
“Fully managed, zero ops overhead, serverless architecture | Rapid prototyping to production for teams wanting no infra management.” Gemini 3.5 Flash · scale prompt · first choice
Also compared
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.