Sold by: Split Software
Switch on the Split Feature Data Platform and deliver software features that matter, fast.
4.5
Overview
Why Choose Split?
In a world where product development teams are pressured to do more with less, Split's Feature Data Platform gives you the confidence to move fast without breaking things.
Set up feature flags and safely deploy to production, controlling who sees which features and when. Connect every flag to contextual data, so you know if your features are making things better or worse, and act without hesitation. Split's Amazon S3 integration makes it easy to bring high-volume customer data and feature flags together - enabling users to seamlessly calculate key metrics, increase the reliability of each release, and run experiments while creating customer feedback loops. Split is a feature management and experimentation partner that takes the extra step with experts to support you, offering online courses to help you learn as you go, and providing a developer-oriented culture that puts our customers at the center.
Whether you're looking to increase your releases, to decrease your MTTR, or to ignite your dev team without burning them out - Change the way the work gets done with Split.
Common use cases include continuous integration/continuous delivery, targeted rollouts, dark launches, canary releases, A/B testing, and ongoing experimentation.
For custom pricing, EULA, or a private contract, please contact aws-marketplace@split.io .
Highlights
- A unified feature flagging and experimentation platform enabling product and engineering teams to reduce cycle times, mitigate release risk, and maximize business impact.
- Split provides enterprises with the speed, control, and data-driven insights they need to get ahead of the competition and get the right features in front of customers with zero downtime.
- Split's Feature Data Platform serves feature flags to more than 6 billion devices worldwide
Details
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Business | Starting at 10 seats and 50,000 Monthly Tracked Keys | $7,200.00 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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By Split Software
By LaunchDarkly
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50
In Agile Lifecycle Management
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10
In Business Intelligence & Advanced Analytics, Generative AI, Continuous Integration and Continuous Delivery
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100
In Testing
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
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AI generated from product descriptions
Feature Flagging and Deployment Control
Ability to set up feature flags and safely deploy to production, controlling which users see which features and when with zero downtime deployment capability.
Experimentation and A/B Testing
Support for A/B testing, canary releases, dark launches, and targeted rollouts to enable data-driven experimentation and feature validation.
Contextual Data Integration
Connection of feature flags to contextual customer data through Amazon S3 integration to enable seamless metric calculation and feature impact analysis.
Release Risk Mitigation
Reduction of cycle times and release risk through continuous integration/continuous delivery workflows and mean time to recovery optimization.
High-Volume Data Processing
Capability to serve feature flags to high-volume distributed systems, supporting more than 6 billion devices with reliable feature delivery at scale.
Cross-Platform Feature Flag Management
Feature flags are cross-platform supported with multi-lingual capabilities and real-time consistent updates across all services.
Production Testing and Experimentation
Ability to test ideas in production on real users with measurement of impact and A/B testing capabilities including experiments on different prompts, parameters, or models.
AI Configuration Management
Runtime control over AI prompts and models enabling safe shipping, testing, and optimization of AI experiences in production without code redeployments.
User Targeting and Segmentation
Targeting engine that customizes applications to different user groups based on any attribute for personalized user experiences.
Real-Time Feature Deployment
Real-time delivery of feature updates and configuration changes across front-end and back-end services without requiring code changes or redeployments.
Feature Flag Management
Open-source feature flag platform enabling controlled feature releases and rollouts to manage deployment risk
Data Governance and Compliance Controls
Market-leading data governance, security, and compliance controls designed for enterprise-grade requirements including FedRamp and air-gapped deployment scenarios
Deployment Flexibility
Support for multiple deployment options including cloud-hosted private instances and self-hosted solutions
Developer Tools and Workflow Integration
Developer-focused tools for testing and deploying new features to production environments with streamlined release process capabilities
Standard contract
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Customer reviews
Harsh Sonkar
Feature flags have supported safer rollouts and now manage risk and governance for cloud releases
Reviewed on Jun 03, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case for Split is for controlled feature releases and rollouts, especially when issues are detected. In addition, I use Split to manage releases for users, and marketing is involved in the process too. I am able to detect issues quickly and respond.
How has it helped my organization?
Split has helped us release features faster and with less risk. Feature flags allow us to separate deployments from releases, enabling gradual rollouts, quick rollbacks, and safer testing. This has reduced production issues, improved team collaboration, and increased confidence in delivering new features. The analytics and experimentation capabilities also support data-driven decisions and better user experiences.
What is most valuable?
The best features Split offers in my experience include the basic feature as well as the my expendence feature. I appreciate its integration with the progressive rollout functionality. Split has positively impacted my organization by reducing governance risk in roaming, raising deliveries.
What needs improvement?
I believe Split can improve by enhancing their onboarding experience and providing a more intuitive UI and analytics for measuring feature impact. One challenge I have encountered is managing a large number of features across the moment, which increases complexity prior to regular cleanup. New team members also need time to understand the feature lab.
For how long have I used the solution?
I have been using Split for about five years.
What other advice do I have?
The key reasons behind my high rating for Split include its development workflow and its ability to help me gain confidence and stability. I find that Split's governance and security are provided through strong governance and security during the rollout based on access for RBAC audit log approval workflow and environment level. This feature ensures that only authorized users can modify feature flags and releases, checking for AI-powered applications. The system can be used safely for monitoring and rigorous rollout. In future development, it maintains control, compliance, and operational transfer receipts. Regarding Split's AI capabilities, I find that poor release helps identify accuracy issues early. As a result, AI features are developed more confidently and with lower risk. My overall rating for this product is 9.5 out of 10.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Harsh Sonkar
Feature flags have transformed how we deliver experiments and release features with confidence
Reviewed on Jun 01, 2026
Review from a verified AWS customer
What is our primary use case?
Split has helped streamline our cloud-native application delivery by enabling safe feature rollouts and controlled releases through feature flags. The ability to separate deployment from release reduces risk, improves testing, and allows faster issue resolution. Its intuitive interface, targeting capabilities, and analytics have improved collaboration across teams and increased confidence in our release process.
How has it helped my organization?
Split helped us accelerate feature releases while reducing deployment risk. By using feature flags and controlled rollouts, we were able to test changes safely, minimize production issues, and respond quickly when problems arose. The platform improved release confidence, enhanced collaboration between teams, and reduced the operational effort required to manage software deployments.
What is most valuable?
Split's best features are feature flag management, controlled rollouts, audience targeting, experimentation, and analytics. Feature flags allow teams to release code safely without exposing features to all users immediately. Controlled rollouts reduce deployment risk, while targeting enables personalized user experiences. The experimentation and analytics capabilities provide valuable insights into feature performance and adoption, helping teams make data-driven decisions and deliver software with greater confidence.
What needs improvement?
Split is a strong feature management platform, but there are opportunities for improvement. Simpler onboarding with guided workflows and beginner-friendly documentation would help new users get started faster. More advanced analytics and reporting could provide deeper insights into feature adoption and experiment outcomes. Streamlining parts of the UI would improve usability at scale, while more flexible pricing and additional out-of-the-box integrations with CI/CD and monitoring tools would further enhance the platform's value.
For how long have I used the solution?
I have personally used Split for 12 months or more.
What do I think about the stability of the solution?
Split is stable.
What do I think about the scalability of the solution?
Split scales effectively across team applications and environments. It can support high-volume feature management, enterprise growth, while maintaining reliability, performance, and operational control.
How are customer service and support?
Customer support is responsive and helpful in addressing issues in a timely manner, and the team provides clear guidance for improving implementation and ongoing usage.
Which solution did I use previously and why did I switch?
Yes, we previously evaluated and used solutions such as LaunchDarkly and open-source feature flag tools. We switched to Split because of its strong combination of feature management, experimentation, governance, and analytics in a single platform. Split's controlled rollout capabilities, targeting features, and enterprise-grade controls provided better visibility and helped us manage releases more effectively while reducing deployment risk.
What's my experience with pricing, setup cost, and licensing?
I have used Split for setup, cost, licensing, and pricing.
Which other solutions did I evaluate?
Before choosing Split, I evaluated alternatives such as LaunchDarkly , Optimizely , Statsig , Harness feature flagging like Split, and ConfigCat, as well as Azure App Configuration. Split was attractive because of the combination of features, management, progressive delivery, experimentation, governance, and analytics in a single platform. Enterprise-grade control, auditing, and capability integration with the cloud environment made it a strong fit for managing and scaling software releases.
What other advice do I have?
Out of those features, I rely most on streamlined features such as management and improving release confidence, and support of a more agile development process. I would recommend Split to organizations looking to implement feature flagging and progressive delivery practices at scale.
Split positively impacts my organization as a well-structured organization focused on helping engineering and product teams deliver software more safely through features, platforms, and experimentation. The platform enables controlled feature rollout, reduces deployment risk, supports data-driven decision-making, and provides additional benefits.
Split demonstrates a strong focus on governance and security, which is critical in enterprise software delivery. The platform provides role-based access control, audit, approval workflow, and controls feature rollout, which helps organizations maintain compliance and reduce automation risk. From an artificial intelligence perspective, there is an opportunity to expand intelligent recommendations, anomaly detection, rollout automation, and prediction based on feature performance data. Drive analytics could help my team make faster, more informed release decisions.
Split delivers accurate, reliable feature management capabilities. The platform provides consistent feature flag evaluation, control, rollout, and operational visibility, helping teams deploy changes with greater confidence and reduced risk.
I advise others looking into using Split to start with a clear feature flag, integration, and governance model. Integrate Split into the development monitoring process to maximize the value of the platform. It is useful for teams seeking faster releasing, lower deployment risk, and better control over feature rollout. I rated this product as a 9 out of 10.
Which deployment model are you using for this solution?
Private Cloud