Open-source vector database

What is Weaviate?

Weaviate helps teams build and scale open-source vector database products.

Category
Open-source vector database
Headquarters
Amsterdam, Netherlands
Founded
2019
Employees
90+ disclosed
Total funding
$67M+ disclosed equity
Valuation
Not publicly disclosed after Series B

What is Weaviate?

Weaviate is a open-source vector database company founded in 2019 and headquartered in Amsterdam, Netherlands.

Weaviate builds open-source vector database infrastructure for teams that need production software, AI, or data workflows rather than one-off prototypes. Revenue is not disclosed; Weaviate discloses 15M+ downloads, 16,300+ GitHub stars, and 4,000+ community members. Its public scale signal is 15M+ downloads and 4,000+ community members.

The company sits in a fast-moving market where buyers care about reliability, security, integration depth, and procurement maturity. Open-source AI-native database. Its position is strongest when customers need a managed platform that shortens engineering time while still fitting into existing cloud, data, and developer workflows.

For sellers, Weaviate is best treated as a scaled technical buyer. Engineering and product leaders influence architecture, finance and operations shape budget, and security or procurement becomes more important as contract size grows.

What does Weaviate offer?

Weaviate's product set centers on Weaviate Database, Weaviate Cloud, Dedicated Cloud.

  • Weaviate Database· Core product
  • Weaviate Cloud· Core product
  • Dedicated Cloud· Core product
  • Weaviate Embeddings· Expansion product
  • Query Agent· Expansion product
  • Engram· Expansion product

How does Weaviate make money?

Weaviate makes money through usage, subscription, committed-capacity, and enterprise contracts depending on customer scale.

Free is $0/month for a small managed cluster. Flex starts at $45/month, Plus starts at $280/month, and Premium starts at $400/month, with vector-dimension and storage usage billed by plan. Enterprise-style dedicated deployments add PrivateLink, HIPAA support, higher SLAs, and support commitments.

Growth is driven by land-and-expand adoption: individual developers or small teams start with self-serve usage, then production workloads create larger commitments, security requirements, support needs, and procurement events. Enterprise customers typically pay for higher limits, private deployment patterns, governance, support, SLAs, and negotiated usage economics.

The unit economics depend on the underlying product category. Software-heavy products expand through seats and usage, while AI infrastructure and GPU-cloud businesses require disciplined capacity planning, reserved commitments, power and data-center execution, and high utilization of expensive compute assets.

Who leads Weaviate?

Weaviate is led by Bob van Luijt, with technical, product, and go-to-market ownership spread across the leadership team.

  • Bob van LuijtCo-founder & CEOCo-founder since 2019Public face of Weaviate and steward of its open-source strategy.
  • Etienne DilockerCo-founder & CTOCo-founder since 2019Leads the technical architecture behind the vector database.
  • Paul de GrijpVP of EngineeringEngineering leadershipRuns engineering execution across cloud and database teams.
  • John TrengroveDirector of Applied ResearchApplied research leadershipLeads research work around retrieval quality and AI-native database behavior.

How do you contact Weaviate's leadership?

Use published company channels first. The personal addresses below are format-following examples using weaviate.io; they should be verified before outreach and are not presented as confirmed personal inboxes.

Email formatfirst@weaviate.io (format-following example, not a verified personal mailbox)

How much funding has Weaviate raised?

Weaviate has $67M+ disclosed equity; its latest disclosed valuation/status is Not publicly disclosed after Series B.

Weaviate's disclosed financing history is concentrated in these major events: 2019-2021 Seed and early financing; Feb 2022 Series A - $16M; Apr 2023 Series B - $50M. The latest disclosed valuation or market status is Not publicly disclosed after Series B.

2019-2021: Seed and early financing. Early investors backed the open-source vector search project and initial cloud business. Feb 2022: Series A - $16M. Led by NEA with Cortical Ventures, Zetta Venture Partners, and others participating. Apr 2023: Series B - $50M. Led by Index Ventures with Battery Ventures and existing investors participating.

The funding signal matters because it defines buying capacity and operating pressure. Late-stage capital usually means new hiring, platform expansion, security upgrades, finance-process maturity, and larger procurement reviews; earlier-stage profiles require tighter ROI and founder-led evaluation.

How did Weaviate get here?

Weaviate's path runs from founding in 2019 through product expansion and its latest financing or public-market milestone.

  1. 2019Company foundedWeaviate begins as an open-source, AI-native database company.
  2. Feb 2022Series A raisedThe company raises $16M to expand cloud and open-source adoption.
  3. Apr 2023Series B raisedWeaviate raises $50M to meet demand for vector databases.
  4. 2024Cloud maturesWeaviate Cloud expands managed deployments across AWS, GCP, and Azure.
  5. 2025AI services addedEmbeddings and Query Agent move more AI workflow into the managed platform.
  6. 2026Engram enters GAWeaviate continues broadening from vector search into AI memory and agent infrastructure.

Who are Weaviate's competitors?

Weaviate competes with category specialists, open-source alternatives, and larger platform vendors.

  • PineconeFully managed vector database with a commercial serverless focus.
  • ChromaLocal-first open-source embedding database with simple developer ergonomics.
  • QdrantRust-based vector search database with managed and self-hosted deployment.
  • Milvus / ZillizOpen-source vector database ecosystem optimized for very large deployments.
  • ElasticEnterprise search incumbent with hybrid search and vector retrieval.

Weaviate — frequently asked questions

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