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Machine Learning · head to head

Seldon vs Semgrep

Seldon logo

Seldon

Machine Learning

Kubernetes model serving whose current version is licensed under the Business Source Licence

From
Free
Rated
-
Full reviewWebsite
Semgrep logo

Semgrep

Cybersecurity

Open-source static analysis tool for finding security bugs and enforcing code standards.

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Semgrep free tier caps out at 10 contributors and 10 repositories.
  • They diverge on capability: Seldon covers Kubernetes custom resources, Semgrep covers Static code scanning.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Seldon and Semgrep actually diverge.

Attributes where Seldon and Semgrep differ
AttributeSeldonSemgrep
PlatformsLinuxweb, api, linux, mac, windows
CategoryMachine LearningCybersecurity
Founded2014Unknown

Identical on both: starting price (Free), pricing model (freemium), 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 Seldon

  • Kubernetes custom resources
  • Inference graphs
  • Traffic strategies
  • Open Inference Protocol
  • Alibi Explain
  • Alibi Detect
  • Kafka-backed pipelines in v2
  • Commercial control plane

Only in Semgrep

  • Static code scanning
  • Supply chain scanning
  • Secrets detection
  • Cross-file analysis
  • AI-powered triage and remediation
  • CI/CD integration

What people use each for

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

Seldon

  • Serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate servicesnot Semgrep
  • Running genuine production experiments where a share of live traffic goes to a candidate model and the results are comparednot Semgrep
  • Regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on laternot Semgrep
  • Organisations with an established Kubernetes platform team who want serving expressed as manifests under existing deployment controlsnot Semgrep

Semgrep

  • Scanning code for security vulnerabilities in CI/CDnot Seldon
  • Detecting vulnerable open-source dependenciesnot Seldon
  • Finding hardcoded secrets before code shipsnot Seldon
  • Enforcing custom code standards with rule setsnot Seldon
  • Prioritizing findings with AI-assisted triagenot Seldon

Where each one falls short

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

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.

Semgrep

  • Free tier caps out at 10 contributors and 10 repositories.
  • Secrets scanning is priced as a separate module ($15/contributor) from Code and Supply Chain.
  • Self-managed repositories and custom CI/CD require the Enterprise tier.
  • AI credits are limited per tier and additional usage requires upgrading.

Pricing, plan by plan

Seldon

Free
  • Seldon CoreFree
    • Open source
    • Kubernetes deployment
    • Model serving
  • Seldon DeployFree
    • Enterprise features
    • GUI
    • Monitoring

Semgrep

Free
  • FreeFree
    • Up to 10 contributors
    • Code and Supply Chain scanning
    • 60 AI credits total
  • Teams$30/month
    • Code, Supply Chain, or Secrets scanning per contributor
    • Pro rules
    • AI-powered triage and remediation
  • Enterprise$undefined/month
    • On-prem support
    • Custom CI/CD
    • 50 AI credits per developer/month

Which should you pick?

Choose Seldon if

  • You need kubernetes custom resources.
  • You want to start without paying.
  • You work on Linux.
  • You also want inference graphs.
Seldon review

Choose Semgrep if

  • You need static code scanning.
  • You want to start without paying.
  • You work on web, api, linux, mac, windows.
  • You also want supply chain scanning.
Semgrep review

Questions people ask

Is Seldon or Semgrep better?
Neither clearly leads. Seldon starts at Free and Semgrep at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Seldon or Semgrep?
Seldon starts at Free and Semgrep at Free.
Does Seldon or Semgrep run on more platforms?
Seldon runs on Linux. Semgrep runs on web, api, linux, mac, windows.
Can I use Seldon for free?
Both have a free tier, so you can try either at no cost before committing.
What is Seldon best used for?
Seldon is most often used for serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate services, running genuine production experiments where a share of live traffic goes to a candidate model and the results are compared, regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on later, organisations with an established kubernetes platform team who want serving expressed as manifests under existing deployment controls. Of those, serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate services and running genuine production experiments where a share of live traffic goes to a candidate model and the results are compared are not what Semgrep is typically brought in for.
What can Seldon do that Semgrep cannot?
Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol. Semgrep covers Static code scanning, Supply chain scanning, Secrets detection, Cross-file analysis.

Answered from the vendors’ own pages

Seldon: 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.

Semgrep: What does Semgrep cost?

The Free edition covers up to 10 contributors; Teams starts at $30/contributor/month for Code scanning (Supply Chain also $30, Secrets $15); Enterprise is custom-priced.

Source
Seldon: 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.

Semgrep: Is there a free plan, and what are its limits?

Yes, the Free edition supports up to 10 contributors and 10 repositories with Code and Supply Chain scanning plus 60 AI credits total.

Source
Seldon: 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.

Semgrep: How is usage metered?

Pricing is per contributor, defined as someone who made at least one commit to a scanned private repository in the past 90 days.

Source
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.

Semgrep: Is there special pricing for startups?

Yes, Semgrep offers special startup pricing upon request for early-stage companies.

Source
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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