Vector databases · September 2026 Edition
pgvector vs Pinecone
Ten of twelve models named pgvector first on the direct prompt; two named Pinecone. Both were named by all twelve models and pgvector carries 51 labels and Pinecone 58, so the shares are not directly comparable.
Named in one category this edition.
Named in two categories this edition.
First-choice share35%14%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate14%28%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 8; printed, not drawn.
Labels5158A 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 eleven of the twelve direct answers. Qdrant vs pgvector · Qdrant vs Pinecone
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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 twelve models made each the first choice, per way of asking, and how many argued against it.
pgvectorFirst choices, of twelve modelsPinecone
Direct1021 against Pinecone
Paraphrase23
Comparative13
Budget-constrained505 against Pinecone
Scale-constrained12
Negative317 against pgvector · 10 against Pinecone
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.
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 12 modelsThe answer named them together, and the judge labeled each a first choice.Kimi K2Pinecone, pgvector alternatives: Qdrant, Weaviate
pgvector first, Pinecone an alternative
9 of 12 modelsPinecone was named in the answer but not as the choice, or not at all.GPT-5.4 miniQdrant, pgvector alternatives: Milvus / Zilliz Cloud, Pinecone, Weaviate
Gemini 3.5 Flashpgvector alternatives: Pinecone, Qdrant, Weaviate
Perplexity SonarQdrant, pgvector alternatives: Milvus, Pinecone, Weaviate
Grok 4.1 Fastpgvector alternatives: Pinecone, Qdrant
Mistral Smallpgvector alternatives: Pinecone, Qdrant, Weaviate
Llama 4 Maverickpgvector
Qwen 3.7 Flashpgvector alternatives: Pinecone, Qdrant, Weaviate
GLM 4.7 FlashXpgvector alternatives: Pinecone, Qdrant, Weaviate
MiniMax M2.5pgvector alternatives: Pinecone, Qdrant, Weaviate
Pinecone first, pgvector an alternative
1 of 12 modelspgvector was named in the answer but not as the choice, or not at all.Claude Haiku 4.5Pinecone, Qdrant alternatives: Weaviate, pgvector
Neither was the first choice, one was named
1 of 12 modelsThe answer put something else first and named one of the two as an alternative.DeepSeek V4 FlashQdrant, Weaviate alternatives: 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 thirty points.
pgvector46%#1 of 7Pinecone16%#3 of 7Mid-marketThe figures above
pgvector leads by twenty-two points.
pgvector35%#2 of 8Pinecone14%#3 of 8Enterprise
The order flips: Pinecone leads at enterprise.
Pinecone53%#1 of 11pgvector12%#3 of 11What 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.
“When you need very high-scale, pure vector search | It is often recommended for existing Postgres shops, but can be a weaker fit for large-scale semantic search workloads.” Perplexity Sonar · negative prompt · soft negative
“While pgvector is excellent for millions of vectors, it can struggle at scale due to sequential index scans and limited parallelism.” GLM 4.7 FlashX · negative prompt · soft negative
“Be cautious of `pgvector` if you are dealing with tens of millions of high-dimensional vectors with heavy write/update requirements” Gemini 3.5 Flash · negative prompt · soft negative
“The best vector database for a mid-market B2B company is pgvector, which is a PostgreSQL extension. It is the strongest default for mid-market enterprises” Llama 4 Maverick · direct prompt · first choice
“If your application is already backed by PostgreSQL, start with `pgvector`. It is the most common starting point for B2B applications” Gemini 3.5 Flash · paraphrase prompt · first choice
“Choose `pgvector + pgvectorscale` if: You already use PostgreSQL. Adding a dedicated vector database introduces architectural bloat” Gemini 3.5 Flash · comparative 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.
“Specific Targets to Watch Out For: Pinecone (purely managed serverless)... you cannot take your data elsewhere without significant re-architecture.” Qwen 3.7 Flash · negative prompt · hard negative
“Be most cautious about: 1. Pinecone if you value control, portability, or cost predictability.” DeepSeek V4 Flash · negative prompt · hard negative
“Avoid Initially: Pinecone/Weaviate Cloud ... not "limited budget"” Grok 4.1 Fast · budget prompt · hard negative
“I'd recommend starting with pgvector if you're already on PostgreSQL, or Pinecone if you want fully managed with minimal ops overhead” Kimi K2 · direct prompt · first choice
“Pinecone | Managed SaaS (serverless pods) | Zero-ops, low-latency RAG/enterprise AI | Billions | Usage-based; $$ but predictable” Grok 4.1 Fast · scale prompt · first choice
“Start with Pinecone if speed to market and operational simplicity are paramount, or Qdrant if you prefer open-source” Claude Haiku 4.5 · direct prompt · first choice
Comparisons are drawn for the top three products in each category. The output is the models' output; nothing here is a recommendation by the index.