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Elementary-data Review

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Should I use Elementary-data?

Introducing Elementary Runtime: Deeper data-quality and AI workflows, inside your environment. - elementary-data.com

· 5 hours ago

dbt-heavy data teams get real value from the free OSS core, with Cloud available for anomaly alerts and AI validations. Everyone else — especially orgs lacking supply-chain controls after the April 2026 credential-stealing release — should pass.

Confidence

Medium. Based on 15 public sources; many review snippets were truncated, so exact ratings and pricing figures were unavailable.

Ratings

  • Value for money
  • Ease of use
  • Feature depth
  • Support qualityNo support evidence in sources
  • Security posture

Pricing

Free

OSS

ModelNot disclosed
Monthly fees1.1M+
HardwareNot disclosed
Free tierYes
CloudUsage-based (rates not public)

Best for

  • dbt-centric data teams
  • Engineering-led orgs okay self-hosting OSS
  • Teams finding Monte Carlo too pricey
  • Snowflake/BigQuery/Redshift warehouse stacks

Not for

  • Teams not using dbt — the tool is dbt-native end to end
  • Orgs without strict dependency pinning after the 2026 PyPI incident
  • Guess: Non-technical teams wanting no-code, vendor-run dashboards
  • Guess: Small projects with a few tables — dbt tests alone may suffice

Gotchas - check before you buy

high

April 2026: malicious v0.23.3 PyPI/GHCR release stole cloud credentials. Pin versions; audit CI credentials.

medium

Pricing is usage-based with no public rates; expect a sales conversation.

medium

OSS/Cloud split means self-hosting alerting or paying for Cloud.

low

Moves fast — frequent releases may mean upgrade churn.

Pros and cons

Pros

  • Free, self-hosted open-source core
  • Praised for seamless dbt integration
  • Customers call pricing competitive
  • Includes anomaly detection and AI-powered validations
  • Positioned as a cheaper Monte Carlo alternative

Cons

  • Only 18 G2 reviews — thin independent feedback
  • Value collapses without dbt
  • Key features like anomaly detection require paid Cloud
  • April 2026 malicious release eroded package trust

Sources & method

- 15 sources - Vendor-disclosed supply chain incident in April 2026: a malicious PyPI/GHCR release pushed an infostealer targeting data engineers' cloud credentials.

official x4review x7security x4
  • Malicious OSS release v0.23.3 (April 2026), A forged release of the elementary-data PyPI package and GHCR container stole cloud credentials from data engineers; vendor published an incident report.

Key stats

  • Value for money: 4/5

    Rating

  • Free

    Starting price

  • 15

    Sources

  • Analyzed

  • Value for money: 4/5. Free OSS; customers call pricing competitive
  • Ease of use: 4/5. Praised for seamless dbt integration
  • Feature depth: 4/5. Anomaly detection, AI validations, warehouse-native monitors
  • Support quality. No support evidence in sources
  • Security posture: 2/5. 2026 supply-chain breach, vendor disclosed
  • 18 G2 reviews across Elementary's G2 seller page
  • 1.1M+ Monthly PyPI downloads per April 2026 incident coverage
  • Yes (OSS) Free tier self-hosted CLI + dbt package
  • 2 Editions OSS and Cloud

Pricing

OSS

Free

  • Self-hosted dbt package and CLI
  • Community support

Cloud

Usage-based (rates not public)

  • Anomaly detection
  • Alerts and AI validations
  • Hosted runtime

Security

Vendor-disclosed supply chain incident in April 2026: a malicious PyPI/GHCR release pushed an infostealer targeting data engineers' cloud credentials.

  • Malicious OSS release v0.23.3 (April 2026)A forged release of the elementary-data PyPI package and GHCR container stole cloud credentials from data engineers; vendor published an incident report.⁹

What users say

A small but positive review base: users praise seamless dbt integration and competitive pricing, though snippets reveal little negative detail.

Alternatives

Compare Elementary-data with each alternative.

  • dbt built-in tests

    Already in your repo, free — start here before buying anything.

  • Great Expectations

    More control, more setup; heavier code-first validation.

  • Monte Carlo

    Enterprise observability, vendor-run; costs considerably more.

Full analysis

Based on 15 public sources; many review snippets were truncated, so exact ratings and pricing figures were unavailable.

Strong free dbt observability if you run dbt; skip otherwise. Watch the 2026 malicious-PyPI incident.

Methodology

Based on 15 public sources; many review snippets were truncated, so exact ratings and pricing figures were unavailable.

Read how a report is made.

Sources

  1. Elementary Data Reviews 2026 (G2)g2.com
    review
  2. Elementary Data Products — 18 G2 reviewsg2.com
    review
  3. G2 users' pros and consg2.com
    review
  4. Elementary vs Monte Carlo comparisondatastackindex.com
    review
  5. Great Expectations vs Elementarymodern-datatools.com
    review
  6. elementary-data GitHub repogithub.com
    official
  7. Elementary OSS vs. Elementary Cloud docsdocs.elementary-data.com
    official
  8. Elementary pricing pageelementary-data.com
    official
  9. Malicious release of Elementary OSS Python CLI v0.23.3 (vendor report)elementary-data.com
    security
  10. Snyk: malicious PyPI release steals cloud credentialssnyk.io
    security
  11. BleepingComputer: 1.1M-download PyPI package hackedbleepingcomputer.com
    security
  12. StepSecurity: PyPI/GHCR compromise via GitHub Actions injectionstepsecurity.io
    security
  13. AI Data Validations docsdocs.elementary-data.com
    official
  14. Customer story: Improving data observability with dbt tests and Elementaryelementary-data.com
    review
  15. SpotSaaS: dbt-native observability reviewspotsaas.com
    review

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