Databases · head to head
QuestDB vs Seldon
QuestDB
Databases
Fast open source time-series database for high throughput ingestion
- From
- Free
- Rated
- -
Seldon
Machine Learning
Kubernetes model serving whose current version is licensed under the Business Source Licence
- From
- Free
- Rated
- -
The short version
- Each has a real cost: QuestDB open-source edition lacks high-availability, distributed architecture, and enterprise security features; Seldon seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
- They diverge on capability: QuestDB covers High Throughput Ingestion, Seldon covers Kubernetes custom resources.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which QuestDB and Seldon actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), founded (2014).
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 Seldon
- Kubernetes custom resources
- Inference graphs
- Traffic strategies
- Open Inference Protocol
- Alibi Explain
- Alibi Detect
- Kafka-backed pipelines in v2
- Commercial control plane
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 Seldon
- Real-time dashboarding with 32ms time-to-first-row latency for minute-level analyticsnot Seldon
- Applications requiring multi-tier storage (hot ingest, real-time SQL, cold Parquet archive)not Seldon
Seldon
- Serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate servicesnot QuestDB
- Running genuine production experiments where a share of live traffic goes to a candidate model and the results are comparednot QuestDB
- Regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on laternot QuestDB
- Organisations with an established Kubernetes platform team who want serving expressed as manifests under existing deployment controlsnot 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
Seldon
- Seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
- Core v1 remains Apache 2.0 but is in maintenance, so taking the free route means running software that receives no new development while the architecture it belongs to moves on without it.
- Version 2 is a different system rather than a newer release, with different custom resources, a scheduler component and a Kafka-based pipeline model, so migrating from v1 is a re-implementation of every deployment manifest rather than an upgrade.
- Kafka is a dependency for v2 pipelines, so an organisation that does not already operate it takes on a distributed log with its own storage, retention, rebalancing and failure modes purely in order to serve models.
- Everything assumes Kubernetes fluency and the failure modes are Kubernetes failure modes, custom resource version mismatches, an operator that will not reconcile, admission webhooks and resource limits terminating an inference pod mid-request, so it needs a platform engineer rather than a data scientist.
Pricing, plan by plan
QuestDB
FreeNo published plan breakdown. See the QuestDB review.
Seldon
Free- Seldon CoreFree
- Open source
- Kubernetes deployment
- Model serving
- Seldon DeployFree
- Enterprise features
- GUI
- Monitoring
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 Seldon if
- You need kubernetes custom resources.
- You want to start without paying.
- You work on Linux.
- You also want inference graphs.
Questions people ask
- Is QuestDB or Seldon better?
- Neither clearly leads. QuestDB starts at Free and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, QuestDB or Seldon?
- QuestDB starts at Free and Seldon at Free.
- Does QuestDB or Seldon run on more platforms?
- QuestDB runs on Docker, Kubernetes, Cloud (AWS, Azure, GCP). Seldon runs on Linux.
- 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 Seldon is typically brought in for.
- What can QuestDB do that Seldon cannot?
- QuestDB covers High Throughput Ingestion, SQL Support, Time-series Optimization, SIMD Vectorization. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.
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.
SourceSeldon: Is Seldon open source?
Partly, and this is the thing to check before you build on it. Core v1 is Apache 2.0 but in maintenance. Core v2 was moved to the Business Source Licence in 2024, which allows evaluation but not unlicensed production use. Verify the current licence of each component you intend to run, including MLServer and the Alibi libraries.
QuestDB: 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.
SourceSeldon: What is the difference between v1 and v2?
Architecture, not just version number. v2 introduces a scheduler, a different set of custom resources and Kafka-backed pipelines. Manifests, mental model and operations all change, so treat a move as a project.
QuestDB: 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.
SourceSeldon: Do I need Kubernetes?
Yes. It is a Kubernetes-native system and there is no meaningful deployment without a cluster and someone competent to run it.
Seldon: What is MLServer?
Seldon's Python inference server implementing the Open Inference Protocol, usable inside Seldon deployments or on its own. Check its current licence alongside Core's, since the company has moved projects onto the Business Source Licence.
Seldon: Do I have to run Kafka?
For v2 pipelines, yes. If you only need single models served, that dependency is a large amount of infrastructure for the benefit, and a simpler serving layer may be the better answer.
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