Synthetic data software produces artificial records that mimic real tables, free text or patient cohorts, so teams can test, train models and share data without exposing the original.
This guide ranks thirteen products on setup effort, the bill once modules are added, how data and generators can leave, and whether you can buy without a partner.
Vendors can pay for more visibility on this website, for example a higher place in a ranking or more room on a page. Commercial relationships can also affect which products we feature and how prominently. Every vendor link is marked the same, whatever the arrangement behind it. How that works.
In short
What synthetic data software does
Synthetic data software creates artificial datasets that copy the structure or statistics of real data, using rules or trained models, so teams can test, build models and share data.
Our order comes from five tests, taken in turn: effort to set up, what you really pay, what happens to your data on the way out, how locked in you are, and the intended customer. On top of them sits one rule. The top three places are for challengers, which means vendors outside the big names, where the category has any, and the household brands come in from fourth place. Why those five, and why there is no score out of ten, is on the how we work page.
Three separate products for fake data, masked databases and text redaction
Ranked #1 of 13 in Best Synthetic Data Software in 2026.
Free tierPublished pricingNorth America
Tonic.ai lets a buyer start on a self-service plan and still reach database-grade masking later. Fabricate's free plan allows trial runs; Structural adds de-identification and subsetting for real databases.
Cost becomes harder to forecast once all three products are in use, because each meters something different: credits, source gigabytes or words. Check which of the three you actually need before asking for a combined quote.
What stands out
Free plan
Per-volume pricing
Three products
Where it costs you
Structural has no self-service price: Professional and Enterprise are both custom, sized by the volume of connected source data.
Credits in Fabricate are consumed per generation turn, so heavy use moves you from the free plan to pay-as-you-go quickly.
Right for
Developers who want to try generation on a free plan before a database project
Wrong for
Teams wanting a single flat licence across every data type
United StatesFree plan and a monthly Plus tier with published credits for Fabricate; Structural and Textual priced by data volume; Enterprise quoted
Feature-priced synthetic data platform with no charge per generation
Ranked #2 of 13 in Best Synthetic Data Software in 2026.
Self-hostablePricing on requestEurope
Syntho's fixed-fee design suits test data programmes that regenerate often, since extra runs cost nothing extra. The pricing page lists 200-plus mockers, a sensitivity scanner, subsetting, upsampling and a quality report.
It also lists the self-hosted option. The weak point is transparency in practice: despite the page title, amounts sit behind a quote form, and connection counts cap each plan.
What stands out
Feature-based plans
Runs in your environment
Mock and AI methods
Where it costs you
Database connections come in bands of one to five, six to ten and eleven to fifteen, with more on request, so many sources push you up a tier.
The pricing page shows no amounts and no trial, so budget approval has to wait for a sales conversation.
Right for
Teams with several databases wanting a fixed fee and deployment inside their network
Wrong for
Anyone who wants a price list and a login today
NetherlandsQuoted per organisation on three feature-based plans; no consumption charges; self-hosted engine
Singapore vendor of tabular synthetic data, packaged for air-gapped deployment
Ranked #3 of 13 in Best Synthetic Data Software in 2026.
Self-hostablePricing on requestAsia-Pacific
Betterdata covers the full path from tabular models to a deployable package. It lists a tabular foundation model alongside GANs, tree-based and transformer-based generators, plus PII redaction and audits.
The company also says it co-authored Singapore's synthetic data guidelines with the PDPC. What is missing is anything a buyer can verify without a meeting: amounts, plan limits and trial terms.
What stands out
Differential privacy
Air-gapped option
Tabular and relational
Where it costs you
No price or trial is shown on the pages read, so comparing cost with Syntho or Tonic.ai is impossible without a call.
Several customer stories on the site are unnamed (a Tier 1 Asian bank, a luxury maison), which limits what you can check.
Right for
Regulated buyers needing synthetic tables generated inside an isolated network
Wrong for
Small teams that want to self-serve and compare prices
Browser-based random data generator with annual tiers and a Docker option
Ranked #4 of 13 in Best Synthetic Data Software in 2026.
Free tierPublished pricingElsewhere
Mockaroo is the budget end of this guide. Prices are on the page: a free plan, then Silver, Gold and an Enterprise tier that ships as a Docker image for your own private cloud or datacentre.
Limits are measured in rows per file and API records per day. It suits prototypes and demos, but it is not a privacy tool for sensitive production data.
What stands out
Free plan
Annual tiers
Docker image
Where it costs you
The pages read describe schema-based field generators, not models trained on real data, so correlations across columns need hand-written rules.
The top tier is priced per company per year, a large step from the Gold tier, and the legal pages read name no company address.
Right for
Developers filling a test database or mocking an API at a low yearly price
Wrong for
Teams needing statistically faithful copies of production data
Not stated by the vendorFree plan with row limits; three annual tiers with published prices; Enterprise sold as a Docker image for your own cloud or datacentre
Apache-licensed synthetic data SDK with a separate Kubernetes platform
Ranked #5 of 13 in Best Synthetic Data Software in 2026.
Open sourcePricing on requestElsewhere
For engineers, the Apache licence is the draw: the SDK trains locally, reports quality and generates samples, and can import generators into the platform. For procurement it is harder.
The site now carries the words powered by Syntho, the contact page redirects to Syntho, and there is no price page. Treat the SDK and the hosted platform as two separate purchasing decisions, and ask Syntho who operates which.
What stands out
Open source SDK
Kubernetes platform
TabularARGN model
Where it costs you
Ownership is unclear for buyers: enquiries go to Syntho's contact form, and no operating company or country is named.
The pricing page returns not found, so platform costs are unknown, and the SDK is only a library, without the platform's team features.
Right for
Data scientists who want an open-source generator they can run on their own machines
Wrong for
Buyers who need a named company and a price list
Not stated by the vendorOpen source SDK under Apache 2.0; no prices on the pages read for the platform
Test data suite where synthetic generation is one part of masking
Ranked #6 of 13 in Best Synthetic Data Software in 2026.
Pricing on requestEurope
DATPROF places synthetic generation inside a broader test data workflow: mask, subset, provision and analyse. The pricing page says the fixed licence does not change with database size, from 500 GB to 100 TB, and amounts come from a sales form.
Offices are in Groningen and Miami. Expect strong fit for testing and limited depth for machine-learning data, since that is what the pages emphasise.
What stands out
Masking first
Modular licence
50+ generators
Where it costs you
Subsetting, runtime, analysis and virtualisation are listed as separate products, so a full test data stack means adding modules.
The pages read describe generators and seed files rather than models trained to copy a dataset's statistics.
Right for
QA and DevOps teams refreshing masked test databases across many applications
Wrong for
Data scientists who need statistically faithful training data
NetherlandsQuoted per organisation; modular fixed licence price, independent of database size
Trieste synthetic data platform now pitched at clinical evidence
Ranked #7 of 13 in Best Synthetic Data Software in 2026.
Pricing on requestEurope
Aindo's case rests on certification and compliance rather than self-serve features: the about page records the first Europrivacy certification for synthetic data in healthcare.
The platform page covers privacy, completion of missing data and bias balancing, with a local deployment option, though the pages give no detail on setup effort. Anyone outside health data should ask how much of the product still targets general business users.
What stands out
Healthcare focus
Europrivacy certified
Runs locally
Where it costs you
The homepage is organised around pharma, public health and clinical research, so a retailer or bank will find little to evaluate.
No plan, price or trial is shown on the pages read, only a demo request.
Right for
Hospitals, pharma companies and research groups needing synthetic patient cohorts for studies
Wrong for
Non-health buyers wanting plans, prices and a trial
ItalyNo amounts on the site; demo form and contact page
Synthetic data aimed at AI evaluation sets and rare-event testing
Ranked #8 of 13 in Best Synthetic Data Software in 2026.
Self-hostablePricing on requestElsewhere
Rockfish's own case studies on its site cover marketplace propensity models, agent evaluation and an automotive order bank, all framed as testing and training AI. Deployment choices are broad, from your VPC to a Snowflake app.
The gap for buyers is basic company information, which a procurement team will ask for: neither the about page nor the contact page names a country, and prices are absent.
What stands out
Eval data
VPC or on-prem
Snowflake Native App
Where it costs you
The pitch is evaluation and edge-case data, so general test-database masking is not what the pages describe.
There is no pricing page (it returns not found), and no company country is given on the about or contact pages.
Right for
AI teams that need edge-case data to test agents and models
Wrong for
Teams that need masked copies of whole production databases
Not stated by the vendorNothing priced on the site; access sign-up and demo booking
Anonymisation and provisioning platform licensed per connected data source
Ranked #9 of 13 in Best Synthetic Data Software in 2026.
Self-hostablePricing on requestElsewhere
The licensing page makes costs easier to reason about than most: one annual licence per connected source, no cost by records or refreshes, with on-premise deployment as a feature rather than an extra.
Five categories run from open-source engines to mainframe and Salesforce. The honest limit is scope, because the platform's centre is masking with lineage, not generation, so test the synthetic output on your own tables.
What stands out
Per-source licence
On-premise
Discovery and lineage
Where it costs you
Synthetic data is mentioned briefly next to anonymisation, so generation depth is unproven on the pages read.
Licence categories group engines by type, and mainframe or Salesforce sources fall into a Premium tier needing tailored assessment.
Right for
Teams anonymising several databases for test environments, with signed audit evidence
Wrong for
Data science teams that want model-based synthetic data
Not stated by the vendorQuoted per organisation: annual licence per connected source type; no charge per record or refresh
Test data packages for SAP landscapes, priced by gigabytes and sources
Ranked #10 of 13 in Best Synthetic Data Software in 2026.
Pricing on requestNorth America
Synthesized offers three purchase routes: SAP Store, AWS or Google Cloud Marketplace, or a direct subscription. The pricing page is detailed about what drives cost: production data in scope and the number of sources, with copies unlimited.
Terms name a Delaware corporation with its place of business in New York, plus a registered English company. Synthetic generation now sits behind an SAP and agent-testing story, so ask what is available outside SAP.
What stands out
SAP focus
Package pricing
Marketplace purchase
Where it costs you
Package sizes are capped by production data in scope and by source count, so adding systems moves you up a tier.
The site is now organised around SAP and agent testing, which makes general-purpose synthetic data harder to evaluate.
Right for
SAP teams that want fixed packages and a paid proof on their own data
Wrong for
Buyers wanting a general-purpose synthetic data product outside SAP
United StatesQuoted annual packages sized by data in scope and sources; paid 10-day validation first; no usage or token charges
Healthcare data exploration platform with synthetic data as a feature
Ranked #11 of 13 in Best Synthetic Data Software in 2026.
Pricing on requestMiddle East
MDClone's own page describes synthetic data as a feature of ADAMS, available through the platform's process rather than as a tool you embed in a pipeline. It names health-system and research customers in the US, Israel and Europe.
The vendor's claim that its method fully prevents re-identification is its own, and the pages read offer no independent test, so ask for one before relying on it.
What stands out
Healthcare only
ADAMS platform
Synthetic as a feature
Where it costs you
Synthetic data is not available as a separate product, so you buy the exploration platform around it.
No price or trial appears on the pages read, only a short demo offer.
Right for
Health systems wanting clinicians to explore patient data through synthetic copies
Wrong for
Any buyer working outside healthcare and life sciences
IsraelNo price list on the pages read; demo form offered
Synthetic data SDK and Fabric platform, assets now agreed to KPMG
Ranked #12 of 13 in Best Synthetic Data Software in 2026.
Free tierSelf-hostablePublished pricingNorth America
The SDK pricing page is concrete: a free plan with a monthly credit, then credits billed per million data points or per ten thousand tokens. The Fabric page adds self-hosted options on two clouds and on-premise through sales.
The release says the founders are expected to join KPMG, so check support and product commitments in writing before signing, especially for the self-hosted installs.
What stands out
Free community plan
Credit pricing
KPMG deal
Where it costs you
The KPMG release describes using the technology for its own Audit, Tax and Advisory work, so outside roadmap priority is a risk.
Fabric pay-as-you-go and the SDK use different pricing pages and plan structures, which makes the real bill harder to forecast.
Right for
Teams wanting to test synthetic generation on a free plan before committing
Wrong for
Buyers who need a vendor independent of a professional services firm
United StatesFree community plan; pay-as-you-go credits published for the SDK; Enterprise quoted; self-hosted on AWS and Azure marketplaces
Entity-based synthetic data generation across many connected enterprise systems
Ranked #13 of 13 in Best Synthetic Data Software in 2026.
Pricing on requestElsewhere
K2view's pitch is entity consistency: its page says it generates whole business entities so data relationships stay intact across systems. It picks among four methods per use case and lists enterprise apps, files, relational and NoSQL stores, mainframe and cloud sources.
That breadth is the cost: the product is an enterprise platform, with a demo and a product tour in place of a price list, so expect a long evaluation.
What stands out
Entity-based
Four methods
Mainframe sources
Where it costs you
Synthetic data sits inside a larger platform, so a buyer needing only a generator pays for scope they may not use.
No price page was found and the company's country is not stated on the pages read.
Right for
Large organisations needing consistent synthetic customers across many linked systems
Wrong for
Small teams wanting a stand-alone self-serve generator tool
Not stated by the vendorNo price list on the pages read; product tour and demo offered
Synthetic data software creates artificial datasets that copy the structure or statistics of real data, using rules or trained models, so teams can test, build models and share data. Rather than compare features, settle the following points one after another.
01
Work out how much a sales call is worth to you
Prices are public at 3 products (Tonic.ai, Mockaroo, YData) and on request at the remaining 10, so budget time for quotes if your favourite is in that second group.
02
Decide how much the jurisdiction matters
Check the vendor's home market (Elsewhere 5, North America 3, Europe 3, Asia-Pacific 1, Middle East 1), because that is where subpoenas and data requests arrive first, whatever region holds your files.
03
Check the open source options
1 of these are open source: MOSTLY AI. Hosting one yourself trades a subscription for maintenance.
Synthetic data software: rule-based fakes or learned copies of your data
The first split in this market is how the data gets made. Mockaroo and DATPROF build values from field rules, built-in generators and seed files: quick to set up, easy to explain, but correlations between columns are whatever you wrote down. MOSTLY AI, Syntho and Betterdata train models on your real tables and sample new rows, which preserves joint patterns but needs training time, quality reports and a privacy review.
K2view and Syntho offer both routes in one product. Pick on what the data is for: demo databases and form tests rarely need statistical fidelity, while fraud models and analytics do. Ask each vendor to show both approaches on one of your own tables.
Does the product generate from rules, from trained models, or both?
Is a quality or privacy report produced for each run?
Can you test it on one of your own tables before signing?
How Tonic.ai, Syntho and Synthesized meter the bill
Prices here are metered on three different things, which is why quotes are hard to compare. Tonic.ai counts credits for Fabricate, source gigabytes for Structural and words for Textual. Syntho charges by feature bundle and database connections, with no charge per generation. Synthesized sizes packages by production gigabytes in scope and number of sources, with unlimited non-production copies.
Gigantics counts connected source types, and YData bills credits per million data points. A team refreshing test data daily will prefer fixed fees; a team generating once for a model will prefer credits. Ask every vendor for a quote for the same three sources and the same refresh rate, then compare the totals instead of the unit prices.
Is cost based on rows, credits, source size or connections?
What happens to the bill when you add a fourth database?
Is a proof of concept priced separately?
Where the generator runs: Betterdata, Rockfish Data and Gigantics
For banks, insurers and public bodies the deployment model often matters more than the algorithm. Betterdata ships one hardened package for on-premise, air-gapped or cloud use. Rockfish Data runs in your VPC, on-premise or as a Snowflake Native App. Gigantics treats on-premise as a platform feature rather than a licence category, and Syntho says its engine can be self-hosted with the vendor having no access.
Mockaroo only offers a private install through its Docker-based Enterprise tier. Tonic.ai lists self-hosted deployment under Fabricate Enterprise. Cloud-only trials look easy but can stall once security review asks where training data lands. Confirm the install route, the update path and who holds the model weights before committing to a pilot.
Can the whole product run without reaching the vendor's cloud?
Who operates updates and model upgrades when it runs on-premise?
Is the self-hosted tier the same product as the trial?
Specialists and ownership changes: Aindo, MDClone, YData and MOSTLY AI
Some products here are narrower than their category name suggests. Aindo and MDClone are built around health data, and Synthesized now leads with SAP and agent testing. That focus is useful if you match it and a poor fit if you do not. Ownership has also moved. KPMG announced it would acquire YData's IP and technology assets, and Syntho has acquired the MOSTLY AI brand assets, with enquiries routed to Syntho.
Neither change is a reason to avoid the product, but both affect support commitments, roadmaps and who signs your contract. Ask for the legal entity on the order form, a written support commitment for the term, and a data and generator export path if the product is later folded into another portfolio.
Which legal entity signs the contract and provides support?
Does the vendor's current homepage match your use case?
Can you export trained generators or only the generated data?
What goes wrong most often when buying synthetic data software
Buying on a demo of one clean table and only discovering at rollout that joins across twelve tables lose their keys.
Treating a masking-led product such as Gigantics as a model-based generator, then expecting realistic distributions for training data.
Comparing a per-credit price from Tonic.ai or YData with a fixed-fee quote from Syntho without fixing the same volume.
Skipping the ownership check on YData or MOSTLY AI and signing a multi-year term before support commitments are written down.
07
Frequently asked questions
8 answers
What is the best synthetic data software in 2026?
First of 13 on this page is Tonic.ai. Tonic.ai sells three products under one name. Fabricate builds relational data from scratch and has a free plan with monthly credits.
Structural de-identifies, subsets and synthesizes existing databases, and Textual handles free text. Structural and Textual list only custom or volume-based prices, scaling with source data or words processed, so a full rollout means three price lists, not one.
Which synthetic data tools publish their pricing?
3 of the 13, with the pricing model each one publishes:
Tonic.ai: Free plan and a monthly Plus tier with published credits for Fabricate; Structural and Textual priced by data volume; Enterprise quoted.
Mockaroo: Free plan with row limits; three annual tiers with published prices; Enterprise sold as a Docker image for your own cloud or datacentre.
YData: Free community plan; pay-as-you-go credits published for the SDK; Enterprise quoted; self-hosted on AWS and Azure marketplaces.
The remaining 10 sell by quote.
Is there a free synthetic data tool?
Tonic.ai, Mockaroo, YData come with a no-cost entry point, a free plan or a self-hosted edition.
Where are these synthetic data software vendors established?
In 6 countries across 5 regions: Elsewhere 5, North America 3, Europe 3, Asia-Pacific 1, Middle East 1.
Tonic.ai: United States.
Syntho: Netherlands.
Betterdata: Singapore.
Mockaroo: Not stated by the vendor.
MOSTLY AI: Not stated by the vendor.
DATPROF: Netherlands.
Aindo: Italy.
Rockfish Data: Not stated by the vendor.
Gigantics: Not stated by the vendor.
Synthesized: United States.
MDClone: Israel.
YData: United States.
K2view: Not stated by the vendor.
Which synthetic data tools are open source?
MOSTLY AI.
Which synthetic data tools can you host yourself?
Syntho, Betterdata, Rockfish Data, Gigantics, YData. The other 8 are hosted by the vendor only.
What should you use instead of Tonic.ai?
Look at Syntho (made for teams with several databases wanting a fixed fee and deployment inside their network) and Betterdata (made for Regulated buyers needing synthetic tables generated inside an isolated network), which hold places two and three.
Who should not buy Tonic.ai?
Teams wanting a single flat licence across every data type. Structural has no self-service price: Professional and Enterprise are both custom, sized by the volume of connected source data..
Missing from this synthetic data software ranking? Contact us with a short description of the product and its users. Adding it is an editorial choice, and software advice explains what a listing does and does not involve.
