Best Synthetic Datas of 2026

Gretel.ai is the developer-API-first synthetic-data platform for engineering teams whose evaluation centers on programmatic synthesis rather than UI-led workflows. Founded 2019 in San Diego and backed by Greylock, Gretel built around the thesis that synthetic data belongs in the developer toolchain alongside CI/CD pipelines rather than as a UI-driven analyst tool.

Four tiers. Free Developer covers limited credits with synthetic data plus privacy and standard models. Pro at $295 monthly is sticker-priced for solo developers with 1M synthetic records, advanced models including Tabular LLM, and API plus SDK access. Team is custom-quoted around $3.5K monthly with higher rate limits, SSO, custom models, and integrations. Enterprise is custom-quoted around $10K monthly with on-prem deployment, SOC 2, and dedicated CSM.

The load-bearing wedge is the developer-API plus the sticker-priced Pro tier. Where Tonic.ai and MOSTLY AI gate access through enterprise sales motions before showing real numbers, Gretel publishes Pro at $295 monthly on the marketing site; for solo developers and small teams modeling Year 1 budget, Gretel removes the friction. The catch is the smaller US enterprise reference base than Tonic.ai for risk-averse Fortune 500 procurement.

Mockaroo is the developer mock-data platform for QA engineers and developers whose evaluation requires random fake data for test fixtures rather than statistical-fidelity synthesis. Founded 2013 and bootstrapped, Mockaroo built around the thesis that developers writing tests need realistic-looking fake data quickly and cheaply, with sticker pricing rather than enterprise sales motions.

Four tiers. Free covers 1K rows per request and 200 requests per day with CSV, JSON, SQL output and standard data types. Silver at $5 monthly ($60 yearly) opens 10K rows with custom schema saves and API access. Gold at $16.67 monthly ($200 yearly) bumps to 100K rows with higher rate limits and unlimited custom data types. Enterprise at $416.67 monthly ($5K yearly) is on-prem with dedicated tenancy and custom integrations.

The load-bearing wedge is the public sticker pricing plus the QA-fixture focus. Where Tonic.ai, Gretel, MOSTLY AI, and Hazy are enterprise synthesis platforms gating at custom quotes, Mockaroo publishes Silver, Gold, and Enterprise rates on the marketing site; for solo developers and QA engineers, Mockaroo removes the friction. The catch is Mockaroo generates random fake data without statistical fidelity, so it should not be used for ML training or analytics where source-data properties matter.

Faker is the open-source MIT-licensed mock-data library for developers whose evaluation requires zero-cost generation of fake names, emails, addresses, and structured data inside their existing codebase. Started around 2007 across Ruby and Python ecosystems and now spanning Faker.js, Faker (Python), Faker (Ruby), and other community ports, Faker built around the thesis that mock-data generation should be a code library rather than a SaaS service.

Two tiers, both essentially free. Open Source is MIT-licensed across Python, JavaScript, Ruby, and other community ports with multi-language support and standard data types. GitHub Sponsors at $5+ monthly is optional donation supporting core development with community-driven governance.

The load-bearing wedge is the in-codebase library deployment plus the MIT licensing. Where Mockaroo ships a SaaS UI for generating mock data files and Tonic.ai through Hazy ship synthesis platforms, Faker ships a library you import directly in your test suite; for developers writing unit tests and seed data scripts, Faker is the lowest-friction option. The catch is Faker is a code library not a synthesis platform; it generates random data without statistical fidelity and lacks the connector ecosystem the SaaS platforms ship.

Synthea is the healthcare-specific open-source synthetic patient data project for healthcare organizations and federal agencies whose evaluation requires HIPAA-compliant test patient records without exposing real PHI. Started in 2017 and federally funded by MITRE Corporation, Synthea built around the thesis that healthcare synthetic data should be a free public resource governed by a non-profit research institution rather than a SaaS upsell funnel.

Two tiers, both genuinely free. Open Source is Apache 2 licensed for synthetic patient health records with FHIR plus CSV plus CCDA output. MITRE Sponsorship is free MITRE-funded standard health-data models used by federal agencies including CMS and ONC.

The load-bearing wedge is the genuine free Apache 2 licensing plus the healthcare-specific FHIR output. Where Tonic.ai, Gretel, MOSTLY AI, and Hazy ship general-purpose synthesis platforms requiring custom configuration for healthcare-specific schemas, Synthea ships pre-built clinical pathways modeling realistic patient journeys including conditions, medications, encounters, and procedures; for healthcare developers building HIPAA-compliant test datasets, Synthea is the free starting point. The catch is the absence of database connectors; Synthea generates files rather than connecting to live source data.

Tonic.ai is the combined data masking and synthetic-data platform for US enterprise organizations whose evaluation centers on production-data privacy plus development-data realism. Founded 2018 in San Francisco and backed by Insight Partners, Tonic.ai built around the thesis that data masking and synthetic generation share enough primitives that one platform should serve both rather than two separate vendors.

Three tiers. Free trial covers 14 days with standard data masking up to 10GB sample data. Pro is custom-quoted around $3.5K monthly with synthetic data plus masking and Postgres, MySQL, MongoDB connectors. Enterprise is custom-quoted around $12K monthly with multi-region, on-prem, SOC 2, HIPAA, and dedicated CSM.

The load-bearing wedge is the masking plus synthesis bundle plus the US enterprise reference base. Where Gretel and MOSTLY AI focus on synthesis-only and Hazy targets UK enterprise, Tonic.ai serves the US Fortune 500 audience needing both masking for production-data movement and synthesis for ML training; for organizations whose primary problem is staging-environment-with-realistic-data, the bundle eliminates a vendor split. The catch is the Pro tier custom-quoted around $3.5K monthly puts it above SMB budgets.

MOSTLY AI is the privacy-first relational-synthesis platform for European organizations whose evaluation requires GDPR-EU data residency plus relational schema preservation. Founded 2017 in Vienna and backed by Molten Ventures, MOSTLY AI built around the thesis that European synthetic-data buyers should have a vendor that processes data inside the EU jurisdiction rather than pretending US-based vendors satisfy GDPR Schrems II.

Three tiers. Free Trial covers 100K synthetic rows with standard tabular synthesis through a web UI. Pro is custom-quoted around $3.5K monthly with unlimited synthesis, relational synthesis, and privacy-first modeling. Enterprise is custom-quoted around $12K monthly with self-hosted, multi-region, SOC 2, GDPR, and dedicated CSM.

The load-bearing wedge is the relational synthesis plus the EU jurisdiction. Where Tonic.ai and Gretel are US-based and Hazy is UK-based, MOSTLY AI is Austria-based with the deepest relational-synthesis primitives in the category; for European organizations whose data cannot leave EU jurisdiction or whose source data is multi-table relational rather than flat tabular, MOSTLY AI is the procurement-grade choice. The catch is the smaller US reference base for Fortune 500 procurement and the Pro tier custom-quoted around $3.5K monthly.

Hazy is the UK enterprise privacy-first synthetic-data platform for British and European financial-services organizations whose evaluation centers on UK jurisdiction plus air-gapped deployment. Founded 2017 in London and backed by Notion Capital, Hazy built around the thesis that financial-services synthetic data needs UK-based vendor relationships with on-prem and air-gapped deployment options that US vendors cannot offer for FCA-regulated workloads.

Two tiers, both custom-quoted with GBP native pricing. Pro is custom-quoted around $7K monthly (GBP 3K-8K range) with synthetic data plus privacy and Postgres, Snowflake, Databricks connectors. Enterprise is custom-quoted around $19K+ monthly (GBP 15K+) with on-prem, air-gapped, GDPR, ISO 27001, and dedicated CSM.

The load-bearing wedge is the UK jurisdiction plus the air-gapped deployment. Where Tonic.ai, Gretel, MOSTLY AI, and Synthea cover broader audiences, Hazy targets the FCA-regulated UK financial-services audience needing British vendor relationships and air-gapped on-prem; for British banks and insurers, Hazy is the procurement-grade choice. The catch is the loudest enterprise mid-point in this lineup at $7K monthly Pro and the smaller reference base outside UK financial services.