Vespa
Product Capabilities
Hybrid search platform
As of August 27, 2026, Vespa's features: Nine stated capabilities span hybrid search and RAG, with one listed integration; the breadth covers a full search-to-inference pipeline on paper, but buyers should test the integration surface against their own stack before committing.
Backed by 10 dated facts
Every value derives from a dated, sourced capture — open any fact for its source.
Every value derives from a dated, sourced capture — open any fact for its source.
Capabilities
Ad TargetingAuto ScalingHybrid SearchModel InferenceOpen SourceRAGRecommendationTensor SupportVector Search
Integrations
Docker
Features Change Historydated events · values unlock with a key
Feature removed: Ml Inference · high significance
Feature removed: Real Time Updates · high significance
Feature removed: RAG · high significance
Feature removed: Structured Search · high significance
Feature added: Real Time Updates
Feature removed: Real Time Inference · high significance
Feature removed: Visual RAG · high significance
Feature removed: Recommendation · high significance
Every features fact on this pagekey · value · provenance · dated · sourced
| Fact | Value | Provenance | As of | Source |
|---|---|---|---|---|
| features.ad-targeting | Ad Targeting | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.auto-scaling | Auto Scaling | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.hybrid-search | Hybrid Search | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.integration.docker | Docker | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.model-inference | Model Inference | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.open-source | Open Source | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.rag | RAG | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.recommendation | Recommendation | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.tensor-support | Tensor Support | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
| features.vector-search | Vector Search | company stated | 2026-08-27 | vespa.ai/2023-11-01-blossom-funding/ |
Features across Vector DatabasesVespa ranked in place · tap through for each read
| Company | Features read | Facts |
|---|---|---|
| Zilliz | Hybrid search platform | 75 |
| Weaviate | Hybrid search platform | 35 |
| Chroma | Hybrid search platform | 34 |
| Qdrant | Focused feature set | 32 |
| Vectara | Agentic RAG platform | 31 |
| LanceDB | Hybrid search platform | 25 |
| Pinecone | Reranking platform | 23 |
| Activeloop | Focused feature set | 16 |
| Epsilla | Multi-tenancy platform | 14 |
| KDB.AI | Hybrid search platform | 12 |
| TopK | Hybrid search platform | 10 |
| Vespa this record | Hybrid search platform | 10 |
| Turbopuffer | Multi-tenancy platform | 9 |
No observed features facts yet for Marqo, Milvus and MyScale.
Get features for vespa.ai via API / MCPevery field dated and sourced
RESTopen tier
GET https://api.bixel.com/v1/companies/vespa.ai/facts?dimension=features
{
"data": {
"facts": [
{
"key": "features.ad-targeting",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-27",
"source_url": "vespa.ai/2023-11-01-blossom-funding/"
},
{
"key": "features.auto-scaling",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-27",
"source_url": "vespa.ai/2023-11-01-blossom-funding/"
},
{
"key": "features.hybrid-search",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-27",
"source_url": "vespa.ai/2023-11-01-blossom-funding/"
},
{
"key": "features.integration.docker",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-27",
"source_url": "vespa.ai/2023-11-01-blossom-funding/"
},
"…"
]
}
}MCPfor agents
# any MCP client (Claude, agents)
const record = await bixel.get_company_facts({ domain: "vespa.ai", dimension: "features" })
# returns the features record above,
# each value with its source_url + as_of,
# ready to reason overBuild on the company record. One key, REST + MCP, every signal dated and sourced back to the page it came from.
Public record, read from companies' own pages and boards. Every fact dated and sourced; provenance (observed vs company stated) shown inline.