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EmergentDB vs Upstash Vector

EmergentDB

emergentdb.com

Upstash Vector

upstash.com

Side by side

FigureEmergentDBUpstash Vector
Price from$2/mo$0.40/mo
Free planYesYes
Free trial—Yes
Open source——
WebYesYes
LinuxYes—
APIYesYes
Self-hostedYes—
Plans published54
Spec score · Vector Databases8.4 (#5)7.9 (#13)
SupportThe Community plan includes community support.Enterprise features include professional support with a response-time SLA, a dedicated Slack channel, and a dedicated account manager.

Plans

EmergentDB

  • CommunityFree
  • Launch$24 a year
  • Launch$29 a month
  • Scale$66 a year
  • Scale$79 a month

EmergentDB pricing →

Upstash Vector

  • FreeFree
  • Pay as You Go$0.40 a month
  • Fixed$60 a month
  • EnterprisePriced on request

Upstash Vector pricing →

In their own words

EmergentDB

EmergentDB is an open-source, self-hosted vector database under the AGPL-3.0 license, also available as managed cloud. It automatically selects a search strategy for a dataset, without requiring manual tuning. Vector insertion and search are available through REST API endpoints; vectors can also be inserted with the TypeScript SDK, using embeddings from any source. Listed index types are Flat, HNSW, IVF, PQ, and Emergent, and SDK languages include TypeScript and Python. The free Community plan includes unlimited vectors, queries, and writes, plus community support and the Bolt-lite engine. Managed Launch is listed at $24 per year, billed annually, with a 500K-vector limit; Scale is $66 per year, billed annually, with a 2.5M-vector limit and dedicated instance. The site lists ISO 27001, SOC 2 Type II, GDPR, HIPAA-ready status, and US, EU, and Asia-Pacific data residency. It also reports a crash-safe write-ahead log and performance figures for specified workloads.

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Upstash Vector

Upstash Vector is a serverless cloud vector database for applications that need vector search, including NLP, RAG, recommendations, image recognition, clustering and classification. It uses DiskANN for approximate nearest-neighbor queries and also lists FreshDiskANN as an index type. Developers can use its REST API and SDKs, with first-class Python and TypeScript support and additional SDKs for Go and PHP. Similarity options include Euclidean distance, cosine similarity and dot product. Vectors can carry metadata, and query filters can restrict matches using metadata expressions. Hybrid indexes combine dense semantic search with sparse exact-token search and fuse the results. Documented integrations include Vercel AI SDK, Flowise, LangChain, Langflow, LlamaIndex and LlamaParse. The pricing page lists a default top-k limit of 1,000, up to 48 KB of metadata and 1 MB of data per vector. The Free plan allows 10K daily queries or updates and up to 1 GB of data and metadata. Pay as You Go costs $0.40 a month, billed per 100K requests, with separate storage and bandwidth terms. Region availability varies by plan.

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