Databases · head to head
SurrealDB vs Typesense

SurrealDB
Databases
Multi-model database combining documents, graphs, vectors and time-series
- From
- Free
- Rated
- -

Typesense
Databases
Open-source typo-tolerant search engine as an Algolia alternative
- From
- Free
- Rated
- -
The short version
- Each has a real cost: SurrealDB the listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.; Typesense holding the index in memory caps dataset size by available RAM, which becomes expensive at scale
- They diverge on capability: SurrealDB covers Multi-model engine, Typesense covers In-memory index.
- Prices and features above were last checked on 29 August 2026.
Where they differ
Only the attributes on which SurrealDB and Typesense actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).
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 SurrealDB
- Multi-model engine
- ACID transactions
- Hybrid retrieval
- Horizontal scaling
- Multi-region disaster recovery
- FIPS-compliant cryptography
Only in Typesense
- In-memory index
- Typo tolerance
- Faceting and filtering
- Vector search
What people use each for
The jobs each tool is most often brought in to do.
SurrealDB
- AI agent memory and retrieval-augmented generationnot Typesense
- Applications needing documents, graphs and vectors in one databasenot Typesense
- Knowledge graph construction from unstructured datanot Typesense
- Regulated workloads requiring SOC2/ISO27001/HIPAA-eligible hostingnot Typesense
Typesense
- Replacing Algolia when per-search pricing outgrows the valuenot SurrealDB
- Instant search over a product catalogue or documentation sitenot SurrealDB
- Hybrid keyword and vector search without running two systemsnot SurrealDB
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
SurrealDB
- The listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.
- As a newer multi-model database, it has a smaller ecosystem of drivers, ORMs and community tooling than established single-model databases.
- HIPAA compliance is only available as an Enterprise add-on rather than included in standard paid tiers.
- Combining multiple data models in one engine can add query-planning complexity compared to purpose-built single-model databases.
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
Pricing, plan by plan
SurrealDB
Free- StartFree
- 1 free instance, then from $0.021/hr
- 1GB storage free forever
- Vertical scaling to terabytes
- Scale$0.192/month
- $0.192/node/hr
- Production-grade fault tolerance
- Horizontal scaling to petabytes
- Enterprise$undefined/month
- Self-hosted, custom pricing
- Clustered fault-tolerant deployments
- FIPS-compliant cryptography
Typesense
Free- TypesenseFree
- Full functionality
- Self-hosted
- No usage limits
Which should you pick?
Choose SurrealDB if
- You need multi-model engine.
- You want to start without paying.
- You work on web, api, windows, mac, linux.
- You also want acid transactions.
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.
Questions people ask
- Is SurrealDB or Typesense better?
- Neither clearly leads. SurrealDB starts at Free and Typesense at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, SurrealDB or Typesense?
- SurrealDB starts at Free and Typesense at Free.
- Does SurrealDB or Typesense run on more platforms?
- SurrealDB runs on web, api, windows, mac, linux. Typesense runs on Linux, macOS, Docker, Self-hosted.
- Can I use SurrealDB for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is SurrealDB best used for?
- SurrealDB is most often used for ai agent memory and retrieval-augmented generation, applications needing documents, graphs and vectors in one database, knowledge graph construction from unstructured data, regulated workloads requiring soc2/iso27001/hipaa-eligible hosting. Of those, ai agent memory and retrieval-augmented generation and applications needing documents, graphs and vectors in one database are not what Typesense is typically brought in for.
- What can SurrealDB do that Typesense cannot?
- SurrealDB covers Multi-model engine, ACID transactions, Hybrid retrieval, Horizontal scaling. Typesense covers In-memory index, Typo tolerance, Faceting and filtering, Vector search.
Answered from the vendors’ own pages
SurrealDB: What does SurrealDB cost?
SurrealDB Cloud's Start plan is free with one free instance (then from $0.021/hr), the Scale plan runs $0.192/node/hr for production workloads, and Enterprise self-hosted deployments use custom pricing.
SourceTypesense: Is Typesense free?
The engine is open source and free to self-host. Typesense Cloud is a paid managed option.
SurrealDB: Is there a free plan and what are its limits?
Yes, the Start plan includes one free instance with 1GB of storage free forever and 1GB of outbound data transfer per month, aimed at prototypes and development.
SourceTypesense: 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.
SurrealDB: How is billing handled?
Customers are invoiced monthly based on actual usage in a pay-as-you-go model with no long-term commitments, though commitment-based discounts are available.
SourceTypesense: Does Typesense support vector search?
Yes, including hybrid search combining keyword and semantic matching in one query.
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