Values and mock APIs
Start close to the test: code-level values or a schema-based service.
Selection criteria and alternativesThe test data selection guideTest data management tools,
Test data management tools,
matched to your needs.
Choose by the job you need done. Compare documented capabilities, deployment models and limits — with the sources open beside you.
Which test data tools fit your use case?
A starting shortlist by task. Follow each profile for strengths, trade-offs and sources.
Reusable business scenarios
Make edge cases explicit and keep generation rules reviewable.
Selection criteria and alternativesShared model-based workflows
Evaluate project ownership, automated execution and run evidence together.
DATAMIMIC Enterprise Platform · Synthesized TDK
Selection criteria and alternativesMasked database subsets
Check source selection, relationships and transformations as one workflow.
Tonic Structural · DATPROF Privacy
Selection criteria and alternativesVirtual copies and refresh
Evaluate a virtualized database when copy, refresh and rewind are central.
Selection criteria and alternativesSQL Server fixtures
Start with schema-aware generation and verify your exact database version.
Redgate SQL Data Generator · ApexSQL Generate by Quest
Selection criteria and alternativesEditorial selections, not a benchmark ranking. Tools may fit several workflows. For learned datasets, use the ML guide. ML dataset evaluation
Find your shortlist
Alphabetical, not ranked. Select 2–4 tools for a side-by-side comparison.
28 Tools
Product status changed
ApexSQL Generate by Quest
Database generatorsApexSQL Generate creates SQL Server test data using random, regex, and incremental column generators. Quest presents it in SQL DevOps; latest located release notes are version 2022.02.x.
Sources reviewed
Benerator
Model & scenario generation · Developer toolsBenerator is rapiddweller's Java/XML model-based generator for synthetic data and processing existing data. It targets files, databases, and messaging systems and supports custom extension through SPIs.
Sources reviewed
CA Test Data Manager
Enterprise TDMBroadcom documentation continues to identify CA Test Data Manager and current 4.11 support material. Its documented workflows include profiling, data masking, subset extraction and test-data provisioning; synthetic generation is described in vendor collateral.
Sources reviewed
CloudTDMS
Model & scenario generationCloudTDMS is a hosted, no-code synthetic test-data factory that profiles structures and patterns, defines data models, generates datasets, and connects to databases, files, and SaaS tools.
Sources reviewed
DATAMIMIC CE
Developer tools · Model & scenario generationDATAMIMIC CE is a pip-installable Python developer tool for model-driven generation, SQL-selected source subsets and explicit field transformations. Its Python API, CLI and optional MCP adapter support local, CI and agent-assisted workflows. CE has its own execution core, separate from EE.
Sources reviewed
DATAMIMIC Enterprise Platform
Enterprise TDM · Model & scenario generationDATAMIMIC Enterprise Platform combines customer-owned data models with enterprise execution governance. Rule Sets, source transformations and ML generators can be combined in one engineering project, authored through IDE, LSP and agents, with execution provenance managed by the Platform.
Product status changed
Datanamic Data Generator
Database generatorsDatanamic Data Generator creates schema-aware rows for nine platforms, with direct inserts or SQL, customizable generators, and foreign-key integrity. Vendor says it is no longer a core product.
Sources reviewed
DATPROF Privacy
Enterprise TDMDATPROF Privacy is a proprietary database masking and generation tool. It can mask existing database values or generate new rows while preserving constraints; DATPROF Subset is a distinct product for database subsetting.
Sources reviewed
Delphix
Enterprise TDMPerforce Delphix combines enterprise data virtualization, masking and centralized delivery controls. Its separate Synthetic Data product became generally available in release 2026.2, according to Perforce’s September 2026 release updates.
Sources reviewed
DTM Data Generator
Database generatorsDTM Data Generator creates database test data and scrambled values with schema-aware relationships, repeatable mode, and SQL/file output. Features vary by edition; scrambling and a bundled masking-tool license are Enterprise-only.
Sources reviewed
Faker
Developer toolsFaker is a code library for generating locale-aware fake values such as people, addresses, dates, and identifiers. Python Faker and JavaScript Faker are separate implementations with distinct documentation and releases.
Sources reviewed
generatedata.com
Developer toolsgeneratedata.com is a browser-based configurable generator and an open-source downloadable application. The current repository describes roughly 30 data types and 12 export types; accounts on the hosted site add saved datasets and higher-volume generation.
Sources reviewed
GenRocket
Model & scenario generation · Enterprise TDMGenRocket is an enterprise synthetic test-data automation platform: engineers design reusable test-data cases in its cloud portal, then distributed runtimes generate data on demand.
Product status changed
Gretel / NVIDIA
AI & ML datasetsGretel was acquired by NVIDIA in 2025; NVIDIA now positions synthetic-data generation for agentic AI through NeMo. The availability of Gretel's former standalone platform is unconfirmed.
Sources reviewed
Informatica TDM
Enterprise TDMInformatica's documented TDM product is a web-based interface for data discovery, subsetting, masking and data generation. The 10.5.x documentation describes workflows and generation rules; distinguish this release line from separately marketed cloud services.
Sources reviewed
IRI RowGen
Database generators · Model & scenario generationIRI RowGen synthesizes and populates structurally correct test data for relational databases, files, reports, and semi-structured targets. Jobs use metadata, generation rules, and the CoSort engine; it can blend generated and selected real values.
Sources reviewed
Mockaroo
Developer tools · Model & scenario generationMockaroo is a hosted test-data generator with configurable schemas, browser downloads, APIs, mock API routes, datasets, and de-identification. Output formats and row or request limits depend on the selected workflow and plan.
Sources reviewed
Redgate SQL Data Generator
Database generatorsRedgate SQL Data Generator creates schema-aware synthetic rows for SQL Server and supported hosted deployments, with foreign-key consistency, custom generators, command-line automation, and fixed-seed repeatability.
Sources reviewed
Redgate Test Data Manager
Enterprise TDMRedgate Test Data Manager prepares masked, subsetted database copies through Anonymize and Subsetter. It is a separate product from Redgate SQL Data Generator.
Limited current evidence
RNDGen
Developer toolsRNDGen offers web-based random, synthetic and simulated data generators. Detailed capabilities, limits and licensing are not sufficiently described in the accessible official material.
Retired product
SB Data Generator
Database generatorsSB Data Generator was Softbuilder's GUI tool for generating and loading realistic data into selected database tables or whole databases. The vendor retired it as a standalone product and integrated generation into ERBuilder.
Sources reviewed
Solix Test Data Management
Enterprise TDMSolix's current product datasheet centers Test Data Management on configurable, reusable database subsetting and cloning with relational integrity. Solix separately markets data masking; current reviewed TDM collateral does not establish synthetic generation as a core feature.
Abandoned project
Spawner Data Generator
Developer toolsSpawner is an abandoned desktop test-data generator last released in 2016. Its project page documents delimited text and SQL output, configurable random values and sequences, and direct insertion into MySQL 5.x.
Sources reviewed
Synthesized TDK
Enterprise TDM · Model & scenario generationSynthesized's current TDK platform transforms, generates, and subsets production data using configurable workflows, preserving statistical distributions and referential integrity across supported pipelines.
Sources reviewed
TCS MasterCraft DataPlus
Enterprise TDMTCS MasterCraft DataPlus is the DataPlus product within the MasterCraft suite. TCS documents enterprise test-data management spanning sampling, discovery, masking, synthetic generation, versioning, reservation, and reuse.
Sources reviewed
Tonic Fabricate
Model & scenario generationTonic Fabricate uses an AI Data Agent to generate structured data from scratch and export populated unstructured files. Version 4.32.0 adds time-based scenario simulations in Enterprise private preview.
Sources reviewed
Tonic Structural
Enterprise TDMTonic Structural transforms production-derived relational and semi-structured data for development and testing, combining configurable de-identification with referential integrity and data subsetting.
Sources reviewed
Upscene Advanced Data Generator
Database generatorsUpscene Advanced Data Generator creates reusable localized sample data across related tables. Pro uses ADO/ODBC; editions target InterBase, Firebird, MySQL, or Access. Listed version 4.2.0 was released March 2025.
No tools match. Try a broader search or another category.
Useful comparisons
The difference that changes the decision.
Comparison
Faker vs Mockaroo
Code-level values versus hosted schemas and mock APIs
ComparisonTonic Structural vs Delphix
Source transformations versus virtual copy workflows
ComparisonRedgate SQL Data Generator vs Datanamic Data Generator
Database scope, current status and repeatability evidence
ComparisonDATAMIMIC Enterprise Platform vs GenRocket
Compare authoring, runtime and governance boundaries
Evidence before preference
A comparison you can question.
Check the sources, compare the exact editions and use the same business acceptance criteria. A product name alone does not tell you which workflow is included.
Sources and comparison criteria01
Primary sourcesOfficial documentation and current product material are linked.
02
Clear boundariesEdition, release and preview restrictions stay attached to the claim.
03
No invented winnersNo expert scores, fake review stars or untested performance rankings.
Before you choose
Which is the best test data management tool?
The best fit depends on the required workflow. Shortlist a values library for small fixtures, a model generator for explicit business cases, or a managed product for shared provisioning. Require evidence for your exact database, edition and deployment.
Read the decision guideCan open-source tools replace a TDM platform?
They can cover the generation task when your team already manages execution, access and cleanup. Python Faker and DATAMIMIC CE offer different starting points. Compare the operational work you retain before choosing a platform or building those services yourself.
Read the decision guideDoes a seed make test data reproducible?
A seed controls one input. Runtime versions, source data, reference time, execution order and serialization can also matter. Specify whether you need the same cases, values or bytes, then test that property alongside business correctness.
Read the decision guide