Convex entered the Developer Backend & Vector Search Services top ten.
share of answers
Data as of Aug 25, 2026 · Based on 7,013 AI responses · See how Parse measures this
Developer Backend & Vector Search Services
Parse
https://parse.gl
Qdrant has emerged as the leading vector database, particularly praised for its performance and advanced filtering capabilities. This rise displaced longtime leader , reflecting a broader market shift where AI assistants now weigh open-source flexibility and metadata performance more heavily against the ease of managed services.
| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 | Now ranked #1, excelling at advanced metadata filtering and on-premise deployments. | 40% | |
| 2 | Frequently recommended for handling massive, billion-scale vector datasets in production environments. | 38% | |
| 3 | A consistent leader for native hybrid search and multimodal (text and image) queries. | 38% | |
| 4 | No longer the top choice overall, but still leads for managed, low-latency RAG. | 32% | |
| 5 | 31% | ||
| 6 | 31% | ||
| 7 | The top open-source BaaS, seen as the primary | 18% | |
| 8 | 17% | ||
| 9 | A lightweight, developer-friendly option often cited for prototyping and in-memory use. | 17% | |
| 10 | 11% | ||
| 11 | Recommended for ultra-low latency due to its in-memory architecture. | 11% | |
| 12 | 10% | ||
| 13 | Frequently cited as a leading time-series database and a cheaper alternative to InfluxDB. | 9% | |
| 14 | 9% | ||
| 15 | The standard solution for adding vector search natively to an existing | 8% | |
| 16 | 7% | ||
| 17 | 7% | ||
| 18 | 6% | ||
| 19 | 6% | ||
| 20 | 5% | ||
| 21 | 5% | ||
| 22 | 5% | ||
| 23 | 4% | ||
| 24 | 4% | ||
| 25 | 4% |
Who wins on each AI
The same market, seen by two models.
Sources AI cited
medium.com is the page AI reaches for most here, cited in 40% of analyzed answers.
share of answers
Share of supported contexts
share of answers
Share of direct mentions
share of answers
Direct leader mentions
Climbed from #4 to #1 overall between October and March, dominating prompts on ACLs.
Dropped from #1 to #4 between October and March, facing increased competition from Qdrant.
“The default choice for most vector search needs.” → “The leading managed service, praised for ease-of-use but distinguished from performance leaders.”
Emerged as the primary open-source alternative to Firebase for full-stack applications.
Qdrant has emerged as the leading vector database, particularly praised for its performance and advanced filtering capabilities. This rise displaced longtime leader Pinecone, reflecting a broader market shift where AI assistants now weigh open-source flexibility and metadata performance more heavily against the ease of managed services.
Across 7,013 AI responses, Qdrant is mentioned most, named in 40% of them, followed by Milvus (38%) and Weaviate (38%).
Parse measures each brand's mention rate — the share of answers naming it — across 7,013 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
AI assistants initially favored specialized vector databases like Pinecone and
. Since late 2025, responses have shifted to strongly recommend integrated cloud platforms like Bedrock, Google Vertex AI, and Azure AI Search, which offer embeddings as part of a broader, enterprise-ready AI stack.
What’s the best managed embeddings service for enterprise data?
AI assistants initially favored specialized vector databases like Pinecone and
Weaviate. Since late 2025, responses have shifted to strongly recommend integrated cloud platforms like
Amazon Bedrock, Google Vertex AI, and Azure AI Search, which offer embeddings as part of a broader, enterprise-ready AI stack.
The market map
Recommended by need