Databases · head to head
Meilisearch vs Weaviate

Meilisearch
Databases
Fast open-source search engine built for typo tolerance
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Meilisearch not built for log analytics or aggregation-heavy workloads, which is where Elasticsearch remains the answer; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
- They diverge on capability: Meilisearch covers Typo tolerance, Weaviate covers Vector and keyword search.
Where they differ
Only the attributes on which Meilisearch and Weaviate actually diverge.
| Attribute | Meilisearch | Weaviate |
|---|---|---|
| Pricing model | Open source, no licence fee; managed cloud billed separately | freemium |
| Platforms | Linux, macOS, Windows, Docker, Self-hosted | Linux, Mac, Windows, Web |
| Category | Databases | Machine Learning |
| Founded | Unknown | 2019 |
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 Meilisearch
- Typo tolerance
- Search as you type
- Faceted search
- Simple API
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.
Meilisearch
- Adding product or content search to an application without running Elasticsearchnot Weaviate
- Search-as-you-type interfaces where latency is visible to the usernot Weaviate
- Replacing SQL LIKE queries that cannot handle typos or rankingnot Weaviate
Weaviate
- Running a vector database for semantic and hybrid searchnot Meilisearch
- Generating and storing embeddings alongside the objects they describenot Meilisearch
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Meilisearch
- Not built for log analytics or aggregation-heavy workloads, which is where Elasticsearch remains the answer
- Scaling across many nodes is less mature than the older engines it competes with
- Memory use grows with index size, and large datasets need real capacity planning
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
Meilisearch
Free- MeilisearchFree
- 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 Meilisearch if
- You need typo tolerance.
- You want to start without paying.
- You work on Linux, macOS, Windows, Docker, Self-hosted.
- You also want search as you type.
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 Meilisearch or Weaviate better?
- Neither clearly leads. Meilisearch 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, Meilisearch or Weaviate?
- Meilisearch starts at Free and Weaviate at Free.
- Does Meilisearch or Weaviate run on more platforms?
- Meilisearch runs on Linux, macOS, Windows, Docker, Self-hosted. Weaviate runs on Linux, Mac, Windows, Web.
- Can I use Meilisearch for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Meilisearch best used for?
- Meilisearch is most often used for adding product or content search to an application without running elasticsearch, search-as-you-type interfaces where latency is visible to the user, replacing sql like queries that cannot handle typos or ranking. Of those, adding product or content search to an application without running elasticsearch and search-as-you-type interfaces where latency is visible to the user are not what Weaviate is typically brought in for.
- What can Meilisearch do that Weaviate cannot?
- Meilisearch covers Typo tolerance, Search as you type, Faceted search, Simple API. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy.
Answered from the vendors’ own pages
Meilisearch: Is Meilisearch free?
The engine is open source and free to self-host. Meilisearch Cloud is a paid managed service.
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.
SourceMeilisearch: Meilisearch or Elasticsearch?
Meilisearch is far simpler for application search and works well by default. Elasticsearch is the choice when you also need log analytics and heavy aggregations.
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.
SourceMeilisearch: Does it handle typos automatically?
Yes. Typo tolerance is on by default rather than something you configure.
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.
SourceWeaviate: 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.
SourceWeaviate: 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.
SourceRelated pages
More on Meilisearch
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- Weaviate vs Couchbase
- Weaviate vs DuckDB
- Weaviate vs MariaDB
- Weaviate vs Oracle Database
- Weaviate vs DataGrip
- Weaviate vs Firebolt
- Weaviate vs Google Cloud SQL
- Weaviate vs MotherDuck
- Weaviate vs AWS SageMaker
- Weaviate vs Google Vertex AI
- Weaviate vs Azure Machine Learning
- Weaviate vs DataRobot
- Weaviate vs MLflow
- Weaviate vs Snowflake
- Weaviate vs TensorFlow
- Weaviate vs Comet ML
- Weaviate vs Jupyter
- Weaviate vs LangChain
- Weaviate vs Pinecone
- Weaviate vs Python
- Weaviate vs PyTorch
- Weaviate vs scikit-learn
- Weaviate vs Apache Spark MLlib
- Weaviate vs Weights & Biases
- Weaviate vs Alteryx
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