Vector databases · September 2026 Edition
Qdrant vs pgvector
Four of twelve models named Qdrant first on the direct prompt; ten named pgvector. Both were named by all twelve models and Qdrant carries 63 labels and pgvector 51, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
First-choice share37%35%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate5%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#2A position in a field of 8; printed, not drawn.
Labels6351A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Qdrant reading right to left. Rank and label count are printed, not drawn.Weaviate was named alongside these two in ten of the twelve direct answers. Qdrant vs Pinecone · pgvector 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.
QdrantFirst choices, of twelve modelspgvector
Direct410
Paraphrase62
Comparative01
Budget-constrained95
Scale-constrained01
Negative133 against Qdrant · 7 against pgvector
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 Qdrant and pgvector stood in it.
Both were the first choice
2 of 12 modelsThe answer named them together, and the judge labeled each a first choice.GPT-5.4 miniQdrant, pgvector alternatives: Milvus / Zilliz Cloud, Pinecone, Weaviate
Perplexity SonarQdrant, pgvector alternatives: Milvus, Pinecone, Weaviate
Qdrant first, pgvector an alternative
2 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
DeepSeek V4 FlashQdrant, Weaviate alternatives: pgvector
pgvector first, Qdrant an alternative
8 of 12 modelsQdrant was named in the answer but not as the choice, or not at all.Gemini 3.5 Flashpgvector alternatives: Pinecone, Qdrant, 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
Kimi K2Pinecone, pgvector alternatives: Qdrant, Weaviate
GLM 4.7 FlashXpgvector alternatives: Pinecone, Qdrant, Weaviate
MiniMax M2.5pgvector alternatives: Pinecone, Qdrant, Weaviate
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.
pgvector46%#1 of 7Qdrant30%#2 of 7Mid-marketThe figures above
The order flips: Qdrant leads at mid-market.
Qdrant37%#1 of 8pgvector35%#2 of 8Enterprise
What the models said about Qdrant
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Weaviate, Milvus, Pinecone, and Qdrant are all losing adoption share to custom stacks and provider-native retrieval options.” Claude Haiku 4.5 · negative prompt · soft negative
“Vector-only DBs such as Pinecone, Weaviate, Qdrant, Milvus | When you also need SQL/JSON/transactions in the same system” Perplexity Sonar · negative prompt · soft negative
“it may not be the best choice for those that want zero ops overhead” Llama 4 Maverick · negative prompt · soft negative
“For a budget-conscious company, Qdrant or Weaviate are generally recommended. Qdrant offers the best performance-to-cost ratio” MiniMax M2.5 · budget prompt · first choice
“the best default choice is usually Qdrant if you want a production-ready open-source vector database with low operational cost” GPT-5.4 mini · budget prompt · first choice
“Best overall budget pick: Qdrant — it is repeatedly described as the strongest price-performance option” Perplexity Sonar · budget prompt · first choice
What 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
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.