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Databases · head to head

Typesense vs Weaviate

Typesense logo

Typesense

Databases

Open-source typo-tolerant search engine as an Algolia alternative

From
Free
Rated
-
Weaviate logo

Weaviate

Machine Learning

Open-source vector database

From
Free
Rated
-

The short version

  • Each has a real cost: Typesense holding the index in memory caps dataset size by available RAM, which becomes expensive at scale; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • They diverge on capability: Typesense covers In-memory index, Weaviate covers Vector and keyword search.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Typesense and Weaviate actually diverge.

Attributes where Typesense and Weaviate differ
AttributeTypesenseWeaviate
Pricing modelOpen source, no licence fee; managed cloud billed separatelyfreemium
PlatformsLinux, macOS, Docker, Self-hostedLinux, Mac, Windows, Web
CategoryDatabasesMachine Learning
FoundedUnknown2019

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Typesense

  • In-memory index
  • Typo tolerance
  • Faceting and filtering
  • Vector search

Only in Weaviate

  • Vector and keyword search
  • Built-in vectorizers
  • GraphQL API
  • Multi-tenancy
  • Hybrid search
  • OpenAI
  • Hugging Face
  • Cohere

What people use each for

The jobs each tool is most often brought in to do.

Typesense

  • Replacing Algolia when per-search pricing outgrows the valuenot Weaviate
  • Instant search over a product catalogue or documentation sitenot Weaviate
  • Hybrid keyword and vector search without running two systemsnot Weaviate

Weaviate

  • Running a vector database for semantic and hybrid searchnot Typesense
  • Generating and storing embeddings alongside the objects they describenot Typesense

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Typesense

  • Holding the index in memory caps dataset size by available RAM, which becomes expensive at scale
  • Narrower than Elasticsearch by design: no log analytics or complex aggregation pipelines
  • Smaller ecosystem and community than Algolia or Elasticsearch, so fewer integrations exist off the shelf

Weaviate

  • The free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • Billing is per million vector dimensions rather than per record, so wider embeddings cost proportionally more for the same object count
  • Premium is a prepaid contract starting at $400 a month rather than pay as you go
  • Storage rates do not fall consistently with tier, and Premium Dedicated is $0.1505 per GiB against $0.12 on the cheaper Flex plan
  • The Query Agent is metered separately, free to 1,000 requests a month and $30 a month plus overage beyond

Pricing, plan by plan

Typesense

Free
  • TypesenseFree
    • Full functionality
    • Self-hosted
    • No usage limits

Weaviate

Free
  • Open SourceFree
    • Full features
    • Self-hosted
  • ServerlessFree
    • Managed service
    • Auto-scaling

Which should you pick?

Choose Typesense if

  • You need in-memory index.
  • You want to start without paying.
  • You work on Linux, macOS, Docker, Self-hosted.
  • You also want typo tolerance.

Choose Weaviate if

  • You need vector and keyword search.
  • You want to start without paying.
  • You work on Linux, Mac, Windows, Web.
  • You also want built-in vectorizers.

Questions people ask

Is Typesense or Weaviate better?
Neither clearly leads. Typesense starts at Free and Weaviate at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Typesense or Weaviate?
Typesense starts at Free and Weaviate at Free.
Does Typesense or Weaviate run on more platforms?
Typesense runs on Linux, macOS, Docker, Self-hosted. Weaviate runs on Linux, Mac, Windows, Web.
Can I use Typesense for free?
Both have a free tier, so you can try either at no cost before committing.
What is Typesense best used for?
Typesense is most often used for replacing algolia when per-search pricing outgrows the value, instant search over a product catalogue or documentation site, hybrid keyword and vector search without running two systems. Of those, replacing algolia when per-search pricing outgrows the value and instant search over a product catalogue or documentation site are not what Weaviate is typically brought in for.
What can Typesense do that Weaviate cannot?
Typesense covers In-memory index, Typo tolerance, Faceting and filtering, Vector search. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy.

Answered from the vendors’ own pages

Typesense: Is Typesense free?

The engine is open source and free to self-host. Typesense Cloud is a paid managed option.

Weaviate: What pricing options does Weaviate offer?

Weaviate provides a free tier with usage-based pricing, plus enterprise options. Visit the pricing page for detailed information on plans.

Source
Typesense: Why choose Typesense over Algolia?

Cost and control. Algolia charges per search and per record; Typesense can be self-hosted with no per-query fee, at the cost of running it yourself.

Weaviate: Does Weaviate offer customer support?

Yes, support is included with Weaviate's cloud offerings. Enterprise customers receive first-class support from their global team of experts.

Source
Typesense: Does Typesense support vector search?

Yes, including hybrid search combining keyword and semantic matching in one query.

Weaviate: Can I deploy Weaviate on my own infrastructure?

Yes. Weaviate is open source and deployment-agnostic. You can run it in your own cloud environment or use their managed cloud service.

Source
Weaviate: What data security features does Weaviate provide?

Weaviate includes security & governance, RBAC, SOC 2 and HIPAA compliance, along with multi-tenancy and high availability for enterprise requirements.

Source
Weaviate: How do I get started with Weaviate?

Sign up for their cloud tier, create your first dataset, connect an LLM, and build your AI app. Documentation and quickstart guides are available for Python, Go, TypeScript, and JavaScript.

Source
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