Values and mock APIs
Do you need a few values in test code, or a schema and a download?
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.
What should your test data tool do?
Choose the task first. The examples below are starting points; follow the guide to build your shortlist.
Business scenarios and data models
Specify rules, relationships and deliberate edge cases. Check which edition executes the model.
DATAMIMIC Enterprise · GenRocket
Selection criteria and alternativesMasked database subsets
Use selected source rows with related records. Check sensitive fields after transformation.
Tonic Structural · DATPROF Privacy
Selection criteria and alternativesVirtual copies and refresh
Start here when copying, refreshing and resetting existing environments is the task.
Selection criteria and alternativesDatabase fixtures
Which engine, constraints and data volumes must work?
Redgate SQL Data Generator · ApexSQL Generate by Quest
Selection criteria and alternativesLearned synthetic datasets
Train on representative data, then measure distributions, rare cases and disclosure risks. Compare a Python library with a self-hosted platform.
SDV Community / Enterprise · Syntho
Selection criteria and alternativesEditorial examples based on documented workflows. A tool may serve several tasks; these cards do not rank products.
Find your shortlist
Alphabetical, not ranked. Select 2–4 tools for a side-by-side comparison.
34 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
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 local Python runtime for model-based test data. XML models describe rules, relationships and output targets. It also offers Python and CLI interfaces for developer and CI workflows.
Sources reviewed
DATAMIMIC Enterprise Platform
Enterprise TDM · Model & scenario generationDATAMIMIC Enterprise Platform combines test-data engineering in the IDE with central governance and execution. XML models drive generation or transformation. The Platform manages projects, access and run evidence; modules depend on the license.
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.
Sources reviewed
Greenmask
Enterprise TDMGreenmask builds transformed PostgreSQL dumps and related subsets, then restores them into a target database. Your team owns the YAML configuration and any custom transformations.
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.
Product status changed
IBM InfoSphere Optim TDM 11.7
Enterprise TDMIBM InfoSphere Optim 11.7 extracts related subsets from existing databases and prepares them for development and tests. Assess the exact edition and product identifier: announced marketing-end dates differ. Modern IBM Optim TDM is a separate product line.
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
Jailer
Enterprise TDMJailer exports small connected slices of relational databases. A local extraction model controls which rows and related records are included. Export and import filters support transformations and key remapping.
Sources reviewed
K2view Test Data Management
Enterprise TDMK2view prepares test data around business entities such as customers and orders. It selects related data, masks fields and provisions datasets to test environments. Rule-driven generation and a separate AI generation path are documented.
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.
Product status changed
MOSTLY AI Synthetic Data SDK
AI & ML datasetsMOSTLY AI’s Python SDK trains on tabular or language data and generates samples locally or through a remote SDK endpoint. Syntho acquired the brand assets on 9 June 2026. Confirm former commercial-platform availability separately.
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
SDV Community / Enterprise
AI & ML datasetsSDV learns patterns from existing tables and samples synthetic data through Python. Community includes single-table, multi-table and sequential workflows. Enterprise capabilities and license terms are separate.
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
Syntho
AI & ML datasets · Enterprise TDMSyntho prepares database test data using learned generation, mock values and masking. Teams configure column settings in a workspace and write results to a destination database. This profile covers the Syntho platform separately from the MOSTLY AI SDK.
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 generates test datasets from descriptions through its Data Agent and exports them in several formats. Uploaded examples can enrich generation; assess this separately from Structural’s source-derived workflow.
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
Small fixtures: values in code or hosted schemas
ComparisonK2view Test Data Management vs Delphix
Provision test environments: entity subsets or virtual database copies
ComparisonSDV Community / Enterprise vs MOSTLY AI Synthetic Data SDK
Local learned datasets: model fit, utility and license limits
ComparisonDATAMIMIC Enterprise Platform vs Tonic Structural
Test database data: generate without a production copy or transform source rows
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