Test Data at the Speed of Agile
More than 10 years ago, GenRocket developers set out to design a better way to
generate and manage test data — much more flexible, faster, easier to change and
update, and easily shared between testers and developers. Today, GenRocket has
the leading, patented test data generation system. GenRocket allows for test data
to be modeled easily and synthetically generated on demand using our patented
technology. GenRocket is a self-service system that allows testers to generate
test data in minutes and at a fraction of the cost of other test data management
solutions.
Data Sheet
The Future of Test Data Management
Test Data
in Any Format
File formats:
•	 JSON (Flat/Nested)
•	 XML (Flat/Nested)
•	 Delimited Files (i.e. CSV)
•	 Excel (XLSX or XLS)
•	 SQL
•	 MyISAM
•	 Fixed File
Memory formats
•	 Arrays
•	 Maps
Realtime formats:
•	 REST
•	 SOAP
•	 JDBC
Packaged Applications:
•	 Salesforce
•	 SAP
•	 JD Edwards
Image formats:
•	 GIF
•	 JPEG
•	 PNG
Databases
•	 IBM DB2
•	 MySQL
•	 Oracle
•	 SQL Server
•	 Sybase
•	 Many more
GenRocket is always adding
support for new formats.
Reach out and ask about your
format today.
Model data in the cloud, generate data locally
GenRocket was designed to meet the needs of enterprises. The GenRocket
ecosystem protects your test data by making it only possible to generate your
test data inside your corporate environment. GenRocket is made up of two
applications — a web application and a local runtime. Below is how synthetic
test data generation works with the GenRocket platform. GenRocket Web can be
hosted on our public cloud or your on-premise environment.
1.GenRocket Web: Users use the web application to model a
representation of their data as GenRocket Domains. No sensitive data is
uploaded to GenRocket Web.
2.GenRocket Scenario: GenRocket encrypted Scenarios are a set of
instructions that the GenRocket Runtime uses to generate synthetic test
data.
3.Corporate Firewall: The Scenario is downloaded inside your corporate
environment which follows your specified security requirements.
4.Local Machine + GenRocket Runtime: Users run GenRocket
Scenarios on their local machine or server with the GenRocket Runtime to
generate test data.
5.Test Data: Users can now use the generated test data for their testing
needs.
GenRocket, Inc.
2930 East Ojai Ave Ojai, CA 93023 USA | www.GenRocket.com | Info@GenRocket.com | (805) 836-2879
Classic TDM Solutions GenRocket
1. Delivery of Test Data is too slow:
Pruning test data is a slow process which
result in wait times of days or weeks for
testers to start testing.
2. Low Quality Test Data: Delivered
test data sets are not in the correct format,
bulky, and require testers to manually
modify the data to meet their test case.
3. Centralized Process: Companies have
to hire a centralized team to create and/
or prune data for their entire testing team
which can become a bottleneck.
4. Compliance Risk: These tools still
rely on using production data, even if it is
masked, there is room for user error and you
may risk exposing sensitive information.
5. Expensive: Companies can spend
a minimum of ~$400,000 for a basic
implementation of TDM tools on the
market.
1. On-Demand Data: Testers can generate
test data on-demand in real time. This
decreases the wait time of weeks or days for
test data to just minutes.
2. High Quality Test Data: Testers can
easily generate small, efficient, test data sets
to meet each test case. This decreases the
wait time to kick off each test case.
3. Self-Service Process: Anyone can
generate the test data they need on their
local machine. Companies no longer need
specialized resources to manage test data.
4. No risk: Synthetically generated test
data has zero risk because it doesn’t contain
sensitive production data.
5. Affordable: GenRocket was designed to
be affordable for any enterprise. GenRocket
user licenses are ~8% the cost of other
solution licenses.
Reduce your Test Data Efforts from Days to Minutes
We get it, making a decision on a tool for Test Data Management is a hard task.
To help you understand how GenRocket is different, we have outlined the 5 areas
where GenRocket is disrupting both homegrown and current Test Data Management
Solutions.
Here are head-to-head results of building test data by a major financial services firm.
This client is a member of the Fortune 500. Timing is from the moment the project
started to when the test data was in hand. “Test data engineering” means a team of
people using in-house tools to gather and prune production data.
Key Features
Full Referential Integrity
GenRocket’s synthetic test
data generation can handle
simple to very complex
relationship models.
Create Test Data Based
on any Business Logic
Testers are able to build their
complex data requirements
by linking or referencing
other GenRocket components
to meet any business rules
/ logic with full referential
integrity.
All Combinations of Data
Quickly generate all
permutations of data from a
specified set of values or from
a set of values queried from a
set of columns in a database.
Test Data Versioning
Easily copy and then modify
your test data scenarios for
new project releases.
Next Level of Data Masking
GenRocket avoids the
complexities of data masking
by simply replacing sensitive
data with matching, realistic
synthetically generated data.
Generate Big Data
GenRocket can generate a
million rows of test data in
just over a minute.
Integrate into your CI pipeline
You can integrate GenRocket
directly into your CI pipeline
so you can automate your
test data generation for your
automated test suite.
Comparison: Traditional TDM to GenRocket
GenRocket, Inc.
2930 East Ojai Ave Ojai, CA 93023 USA | www.GenRocket.com | Info@GenRocket.com | (805) 836-2879
Test Data Need Volume of Data
Number of
Columns/Elements
Time taken with
original approach
Time taken
with GenRocket
GenRocket Time
Savings
Mandate XML
for high volume
data needs	
50,000 102 8 ~ 16 hours 5 ~ 15 minutes
Minimum of
32x faster
Transactional
data for
functional
testing
1,000 - 40,000
5 tables /
65 columns
16 ~ 40 hours 1 ~ 30 minutes
Minimum of
32x faster
Interface testing
data files	
5,000,000 18	 ~4 hours 10 ~ 25 minutes
Minimum of
10x faster
Start your No-Cost Proof of Concept
Get started by requesting a demo at www.GenRocket.com.
See how GenRocket can solve your test data challenge with a
Proof of Concept.

More Related Content

PDF
GenRocket Demo 1
PDF
GenRocket Feature List
PDF
5 Key Components of Genrocket
PDF
R meetup talk scaling data science with dgit
PPTX
Neo4j GraphDay Munich - Life & Health Sciences Intro to Graphs
PDF
Neo4j GraphDay Munich - Improve Health Research
PPTX
Elastic as a Fundamental Core to Pfizer’s Scientific Data Cloud
PPTX
Acquisition, Storage and Management of Research Data in Chemical Sciences: De...
GenRocket Demo 1
GenRocket Feature List
5 Key Components of Genrocket
R meetup talk scaling data science with dgit
Neo4j GraphDay Munich - Life & Health Sciences Intro to Graphs
Neo4j GraphDay Munich - Improve Health Research
Elastic as a Fundamental Core to Pfizer’s Scientific Data Cloud
Acquisition, Storage and Management of Research Data in Chemical Sciences: De...

What's hot (6)

PPTX
What we do
PDF
BlueHat Seattle 2019 || Are We There Yet: Why Does Application Security Take ...
PDF
Big Data Certification
PPTX
Irving-TeraData: data and science driven big industry-nfdp13
PDF
( Big ) Data Management - Data Quality - Global concepts in 5 slides
PDF
Switc Hpa
What we do
BlueHat Seattle 2019 || Are We There Yet: Why Does Application Security Take ...
Big Data Certification
Irving-TeraData: data and science driven big industry-nfdp13
( Big ) Data Management - Data Quality - Global concepts in 5 slides
Switc Hpa
Ad

Similar to GenRocket Data Sheet (20)

PPTX
Curiosity and Xray present - In sprint testing: Aligning tests and teams to r...
PDF
BizDataX White paper Test Data Management
PDF
Scalable and Repeatable Machine Learning pipelines: A key requirement for you...
PPTX
HyperconvergedFantasyAnalytics
PDF
Building functional Quality Gates with ReportPortal
PDF
Data Driven Testing Is More Than an Excel File
PDF
Types Of Testing Environment In TestGrid.pdf
PDF
IBM InterConnect 2013 Expert Integrated Systems Keynote: Sotiropoulos & Wieck
DOCX
JESSIESEMANA_CV_1
PDF
Automation test bed at offshore to optimize cost, effort and timing for a wor...
PDF
Service Virtualization: What Testers Need to Know
PDF
Completing the Data Equation: Test Data + Data Validation = Success
PDF
SurinderPanwar_Testing.PDF
PPTX
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
PPTX
Jonathon Wright - Intelligent Performance Cognitive Learning (AIOps)
PPTX
Curiosity and Lemontree present - Data Breaks DevOps: Why you need automated ...
PPTX
AcceleTest
PPTX
AcceleTest
PPT
Monitoring IAAS & PAAS Solutions
Curiosity and Xray present - In sprint testing: Aligning tests and teams to r...
BizDataX White paper Test Data Management
Scalable and Repeatable Machine Learning pipelines: A key requirement for you...
HyperconvergedFantasyAnalytics
Building functional Quality Gates with ReportPortal
Data Driven Testing Is More Than an Excel File
Types Of Testing Environment In TestGrid.pdf
IBM InterConnect 2013 Expert Integrated Systems Keynote: Sotiropoulos & Wieck
JESSIESEMANA_CV_1
Automation test bed at offshore to optimize cost, effort and timing for a wor...
Service Virtualization: What Testers Need to Know
Completing the Data Equation: Test Data + Data Validation = Success
SurinderPanwar_Testing.PDF
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
Jonathon Wright - Intelligent Performance Cognitive Learning (AIOps)
Curiosity and Lemontree present - Data Breaks DevOps: Why you need automated ...
AcceleTest
AcceleTest
Monitoring IAAS & PAAS Solutions
Ad

Recently uploaded (20)

PPTX
Microsoft Excel 365/2024 Beginner's training
PDF
Hybrid horned lizard optimization algorithm-aquila optimizer for DC motor
PDF
Zenith AI: Advanced Artificial Intelligence
PDF
NewMind AI Weekly Chronicles – August ’25 Week III
PPTX
Benefits of Physical activity for teenagers.pptx
PPT
What is a Computer? Input Devices /output devices
PPT
Galois Field Theory of Risk: A Perspective, Protocol, and Mathematical Backgr...
PPT
Geologic Time for studying geology for geologist
PDF
A contest of sentiment analysis: k-nearest neighbor versus neural network
PPTX
AI IN MARKETING- PRESENTED BY ANWAR KABIR 1st June 2025.pptx
PDF
sbt 2.0: go big (Scala Days 2025 edition)
PDF
Getting started with AI Agents and Multi-Agent Systems
PDF
UiPath Agentic Automation session 1: RPA to Agents
PDF
Convolutional neural network based encoder-decoder for efficient real-time ob...
PDF
From MVP to Full-Scale Product A Startup’s Software Journey.pdf
PDF
Produktkatalog für HOBO Datenlogger, Wetterstationen, Sensoren, Software und ...
PDF
A Late Bloomer's Guide to GenAI: Ethics, Bias, and Effective Prompting - Boha...
PDF
sustainability-14-14877-v2.pddhzftheheeeee
PDF
Hindi spoken digit analysis for native and non-native speakers
PDF
Architecture types and enterprise applications.pdf
Microsoft Excel 365/2024 Beginner's training
Hybrid horned lizard optimization algorithm-aquila optimizer for DC motor
Zenith AI: Advanced Artificial Intelligence
NewMind AI Weekly Chronicles – August ’25 Week III
Benefits of Physical activity for teenagers.pptx
What is a Computer? Input Devices /output devices
Galois Field Theory of Risk: A Perspective, Protocol, and Mathematical Backgr...
Geologic Time for studying geology for geologist
A contest of sentiment analysis: k-nearest neighbor versus neural network
AI IN MARKETING- PRESENTED BY ANWAR KABIR 1st June 2025.pptx
sbt 2.0: go big (Scala Days 2025 edition)
Getting started with AI Agents and Multi-Agent Systems
UiPath Agentic Automation session 1: RPA to Agents
Convolutional neural network based encoder-decoder for efficient real-time ob...
From MVP to Full-Scale Product A Startup’s Software Journey.pdf
Produktkatalog für HOBO Datenlogger, Wetterstationen, Sensoren, Software und ...
A Late Bloomer's Guide to GenAI: Ethics, Bias, and Effective Prompting - Boha...
sustainability-14-14877-v2.pddhzftheheeeee
Hindi spoken digit analysis for native and non-native speakers
Architecture types and enterprise applications.pdf

GenRocket Data Sheet

  • 1. Test Data at the Speed of Agile More than 10 years ago, GenRocket developers set out to design a better way to generate and manage test data — much more flexible, faster, easier to change and update, and easily shared between testers and developers. Today, GenRocket has the leading, patented test data generation system. GenRocket allows for test data to be modeled easily and synthetically generated on demand using our patented technology. GenRocket is a self-service system that allows testers to generate test data in minutes and at a fraction of the cost of other test data management solutions. Data Sheet The Future of Test Data Management Test Data in Any Format File formats: • JSON (Flat/Nested) • XML (Flat/Nested) • Delimited Files (i.e. CSV) • Excel (XLSX or XLS) • SQL • MyISAM • Fixed File Memory formats • Arrays • Maps Realtime formats: • REST • SOAP • JDBC Packaged Applications: • Salesforce • SAP • JD Edwards Image formats: • GIF • JPEG • PNG Databases • IBM DB2 • MySQL • Oracle • SQL Server • Sybase • Many more GenRocket is always adding support for new formats. Reach out and ask about your format today. Model data in the cloud, generate data locally GenRocket was designed to meet the needs of enterprises. The GenRocket ecosystem protects your test data by making it only possible to generate your test data inside your corporate environment. GenRocket is made up of two applications — a web application and a local runtime. Below is how synthetic test data generation works with the GenRocket platform. GenRocket Web can be hosted on our public cloud or your on-premise environment. 1.GenRocket Web: Users use the web application to model a representation of their data as GenRocket Domains. No sensitive data is uploaded to GenRocket Web. 2.GenRocket Scenario: GenRocket encrypted Scenarios are a set of instructions that the GenRocket Runtime uses to generate synthetic test data. 3.Corporate Firewall: The Scenario is downloaded inside your corporate environment which follows your specified security requirements. 4.Local Machine + GenRocket Runtime: Users run GenRocket Scenarios on their local machine or server with the GenRocket Runtime to generate test data. 5.Test Data: Users can now use the generated test data for their testing needs. GenRocket, Inc. 2930 East Ojai Ave Ojai, CA 93023 USA | www.GenRocket.com | Info@GenRocket.com | (805) 836-2879
  • 2. Classic TDM Solutions GenRocket 1. Delivery of Test Data is too slow: Pruning test data is a slow process which result in wait times of days or weeks for testers to start testing. 2. Low Quality Test Data: Delivered test data sets are not in the correct format, bulky, and require testers to manually modify the data to meet their test case. 3. Centralized Process: Companies have to hire a centralized team to create and/ or prune data for their entire testing team which can become a bottleneck. 4. Compliance Risk: These tools still rely on using production data, even if it is masked, there is room for user error and you may risk exposing sensitive information. 5. Expensive: Companies can spend a minimum of ~$400,000 for a basic implementation of TDM tools on the market. 1. On-Demand Data: Testers can generate test data on-demand in real time. This decreases the wait time of weeks or days for test data to just minutes. 2. High Quality Test Data: Testers can easily generate small, efficient, test data sets to meet each test case. This decreases the wait time to kick off each test case. 3. Self-Service Process: Anyone can generate the test data they need on their local machine. Companies no longer need specialized resources to manage test data. 4. No risk: Synthetically generated test data has zero risk because it doesn’t contain sensitive production data. 5. Affordable: GenRocket was designed to be affordable for any enterprise. GenRocket user licenses are ~8% the cost of other solution licenses. Reduce your Test Data Efforts from Days to Minutes We get it, making a decision on a tool for Test Data Management is a hard task. To help you understand how GenRocket is different, we have outlined the 5 areas where GenRocket is disrupting both homegrown and current Test Data Management Solutions. Here are head-to-head results of building test data by a major financial services firm. This client is a member of the Fortune 500. Timing is from the moment the project started to when the test data was in hand. “Test data engineering” means a team of people using in-house tools to gather and prune production data. Key Features Full Referential Integrity GenRocket’s synthetic test data generation can handle simple to very complex relationship models. Create Test Data Based on any Business Logic Testers are able to build their complex data requirements by linking or referencing other GenRocket components to meet any business rules / logic with full referential integrity. All Combinations of Data Quickly generate all permutations of data from a specified set of values or from a set of values queried from a set of columns in a database. Test Data Versioning Easily copy and then modify your test data scenarios for new project releases. Next Level of Data Masking GenRocket avoids the complexities of data masking by simply replacing sensitive data with matching, realistic synthetically generated data. Generate Big Data GenRocket can generate a million rows of test data in just over a minute. Integrate into your CI pipeline You can integrate GenRocket directly into your CI pipeline so you can automate your test data generation for your automated test suite. Comparison: Traditional TDM to GenRocket GenRocket, Inc. 2930 East Ojai Ave Ojai, CA 93023 USA | www.GenRocket.com | Info@GenRocket.com | (805) 836-2879 Test Data Need Volume of Data Number of Columns/Elements Time taken with original approach Time taken with GenRocket GenRocket Time Savings Mandate XML for high volume data needs 50,000 102 8 ~ 16 hours 5 ~ 15 minutes Minimum of 32x faster Transactional data for functional testing 1,000 - 40,000 5 tables / 65 columns 16 ~ 40 hours 1 ~ 30 minutes Minimum of 32x faster Interface testing data files 5,000,000 18 ~4 hours 10 ~ 25 minutes Minimum of 10x faster Start your No-Cost Proof of Concept Get started by requesting a demo at www.GenRocket.com. See how GenRocket can solve your test data challenge with a Proof of Concept.