Databases · head to head
QuestDB vs Vespa

QuestDB
Databases
Fast open source time-series database for high throughput ingestion
- From
- Free
- Rated
- -

Vespa
Databases
Distributed AI search platform for retrieval, ranking, and inference
- From
- Free
- Rated
- -
The short version
- Each has a real cost: QuestDB open-source edition lacks high-availability, distributed architecture, and enterprise security features; Vespa pricing not publicly listed, requires contacting sales
- They diverge on capability: QuestDB covers High Throughput Ingestion, Vespa covers Vector search.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which QuestDB and Vespa 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 QuestDB
- High Throughput Ingestion
- SQL Support
- Time-series Optimization
- SIMD Vectorization
- Column-oriented Storage
- Built-in Web Console
- InfluxDB Line Protocol
- PostgreSQL
Only in Vespa
- Vector search
- Text and structured search
- Machine-learned ranking
- Real-time serving
- SQL interface
- Automatic scaling
- Open-source
What people use each for
The jobs each tool is most often brought in to do.
QuestDB
- Time-series analytics ingesting up to 20M rows/second from IoT sensors or financial data feedsnot Vespa
- Real-time dashboarding with 32ms time-to-first-row latency for minute-level analyticsnot Vespa
- Applications requiring multi-tier storage (hot ingest, real-time SQL, cold Parquet archive)not Vespa
Vespa
- Build RAG systems with semantic search over documentsnot QuestDB
- Power e-commerce search with ML rankingnot QuestDB
- Create recommendation engines for personalizationnot QuestDB
- Implement real-time search for news or feedsnot QuestDB
- Deploy private semantic search over sensitive datanot QuestDB
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
QuestDB
- Open-source edition lacks high-availability, distributed architecture, and enterprise security features
- Enterprise edition pricing not published; requires contacting sales for custom quote
- Ingestion limit of 20M rows/sec platform-dependent; may not scale to extreme throughput requirements
Vespa
- Pricing not publicly listed, requires contacting sales
- Steeper learning curve compared to simpler search tools
- Operational complexity for self-hosted deployments
- Smaller ecosystem compared to cloud-native alternatives
Pricing, plan by plan
QuestDB
FreeNo published plan breakdown. See the QuestDB review.
Vespa
FreeNo published plan breakdown. See the Vespa review.
Which should you pick?
Choose QuestDB if
- You need high throughput ingestion.
- You want to start without paying.
- You work on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
- You also want sql support.
Choose Vespa if
- You need vector search.
- You want to start without paying.
- You work on Cloud, Self-hosted.
- You also want text and structured search.
Questions people ask
- Is QuestDB or Vespa better?
- Neither clearly leads. QuestDB starts at Free and Vespa at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, QuestDB or Vespa?
- QuestDB starts at Free and Vespa at Free.
- Does QuestDB or Vespa run on more platforms?
- QuestDB runs on Docker, Kubernetes, Cloud (AWS, Azure, GCP). Vespa runs on Cloud, Self-hosted.
- Can I use QuestDB for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is QuestDB best used for?
- QuestDB is most often used for time-series analytics ingesting up to 20m rows/second from iot sensors or financial data feeds, real-time dashboarding with 32ms time-to-first-row latency for minute-level analytics, applications requiring multi-tier storage (hot ingest, real-time sql, cold parquet archive). Of those, time-series analytics ingesting up to 20m rows/second from iot sensors or financial data feeds and real-time dashboarding with 32ms time-to-first-row latency for minute-level analytics are not what Vespa is typically brought in for.
- What can QuestDB do that Vespa cannot?
- QuestDB covers High Throughput Ingestion, SQL Support, Time-series Optimization, SIMD Vectorization. Vespa covers Vector search, Text and structured search, Machine-learned ranking, Real-time serving.
Answered from the vendors’ own pages
QuestDB: How much does QuestDB Enterprise cost?
QuestDB does not publish specific pricing for the Enterprise tier. Customers must contact QuestDB via their enterprise contact form to receive a custom quote.
SourceVespa: Is Vespa open-source?
Yes, Vespa is open-source under the Apache 2.0 license. The code is available on GitHub, and you can self-host or use the managed cloud service.
SourceQuestDB: Does QuestDB offer a free version?
Yes, QuestDB Open Source is completely free and recommended for evaluation, prototyping, and pilot projects. Enterprise features, high availability, security, and dedicated support require the paid Enterprise tier.
SourceVespa: What latency can Vespa achieve?
Vespa is designed for sub-100 millisecond latencies with thousands of queries per second, suitable for real-time search and recommendation applications.
SourceQuestDB: What deployment options does QuestDB offer?
QuestDB offers open source deployment, Enterprise deployment, and Bring Your Own Cloud (BYOC) deployment. Pricing details for BYOC and Enterprise tiers are not published and require direct contact with sales.
SourceVespa: Does Vespa support vector search?
Yes, Vespa provides native vector search capabilities alongside text, structured data, and tensor operations for building comprehensive search and AI applications.
SourceVespa: What is the pricing model for Vespa Cloud?
Vespa Cloud pricing is not publicly listed and requires contacting their sales team to discuss your specific use case and scale requirements.
SourceRelated pages
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