Upstash Vector
Upstash Vector: A low-cost serverless vector database with hybrid search and flexible usage pricing. Ranked #15 of 27 in Vector Databases by our editors (7.9/10); pricing: Free plan; best for low-cost serverless vector workloads.
At a glance
- Editor score7.9 / 10
- PricingFree plan
- Best forLow-cost serverless vector workloads
- Free planYes
- Paid from$60/mo
- DeploymentCloud
- Facts checked22 Sep 2026
Where it wins
- Free plan includes 10,000 daily queries and updates
- Supports dense, sparse, and hybrid vector indexes
- REST API, namespaces, filtering, and DiskANN search
Where it doesn't
- Free plan allows only 1 GB of total data
- Verified integration coverage is limited to the Vercel AI SDK
- Higher-capacity plan pricing is not shown in the published plan details
Our verdict on Upstash Vector
Upstash Vector is a fully managed, serverless vector database for developers building semantic search, retrieval-augmented generation, and other AI applications. It supports REST access and official SDKs for Python, TypeScript, Go, and PHP. The service stores vectors, metadata, and text data, while namespaces help organize records. It is designed for cloud workloads that need similarity search without managing database infrastructure directly.
Pricing is structured across Free, Pay as You Go, Fixed, and Pro plans. The Free plan includes one database, 10,000 daily queries and updates, a maximum of 1,536 dimensions, and 1 GB of total data. Pay as You Go starts at $0.40 per 100K requests, raises the maximum to 3,072 dimensions, and removes the daily query and update limit. The Fixed plan costs $60 per month and includes 1 million daily queries and updates, 3,072 dimensions, 50 GB of total data, and a 99.9% uptime SLA. Pro supports up to 5,000 dimensions, 100 billion vectors × dimensions, unlimited namespaces, and a 99.99% uptime SLA.
Its strongest technical fit is for applications that need more than basic dense-vector retrieval. Upstash Vector supports dense, sparse, and hybrid indexes, cosine, Euclidean, and dot-product similarity metrics, metadata filtering with filter expressions, and DiskANN-based approximate nearest-neighbor search. Developers can use Upstash-hosted embedding models or custom embeddings. Choose it for serverless AI workloads, semantic search, or retrieval-augmented generation where usage-based pricing and REST access matter. Teams seeking a broader verified integration ecosystem or a small fixed-scope database may prefer another option.
Your product? Our editors can test Upstash Vector in depth and publish a review, labelled as paid · from $149/mo →
Upstash Vector pricing
All 4 Upstash Vector plans and prices →
Upstash Vector fact sheet
| Free plan | Yes |
|---|---|
| Paid from | $60/mo |
| Deployment | Cloud |
| Hybrid search | Yes |
| Metadata filtering | Yes |
| Sparse vectors | Yes |
| Maximum dimensions | 3072 dimensions |
| Index types | DiskANN, FreshDiskANN |
| SDK languages | Python, TypeScript, Go, PHP |
| Deployment | Cloud |
| Platforms | Web |
| Compliance & security | GDPR |
| Support | Email, Community, Docs |
| Built for | Solo, Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 6 integrations: Vercel AI SDK, LangChain, LlamaIndex, LlamaParse, Flowise, Langflow |
| Pricing | Free plan (source) |
| Website | upstash.com |
| Facts checked | 22 Sep 2026 |
Upstash Vector integrations
Upstash Vector lists 6 integrations on its own site.
- Vercel AI SDK
- LangChain
- LlamaIndex
- LlamaParse
- Flowise
- Langflow
Alternatives to Upstash Vector
- ElasticsearchA broad hybrid-search platform for teams adding vectors to mature analytics stacks.9.3
- Vertex AI Vector SearchA managed Google Cloud option for teams building dense, sparse, and hybrid search.9.2
- VikingDBA cloud vector database with dense, sparse, hybrid, filtered, and multimodal retrieval.9.1
See all Upstash Vector alternatives →
Also Ranked In
Upstash Vector is ranked in 2 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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