Apache JMeter vs Flood.io

Struggling to choose between Apache JMeter and Flood.io? Both products offer unique advantages, making it a tough decision.

Apache JMeter is a Development solution with tags like performance-testing, load-testing, web-application-testing, open-source.

It boasts features such as Load testing, Stress testing, Performance benchmarking, Web - HTTP, HTTPS, SOAP, REST, etc, Database via JDBC, FTP, LDAP, Message-oriented middleware (MOM) via JMS, Mail - SMTP(S), POP3(S) and IMAP(S), Native commands or shell scripts, TCP, Java Objects and pros including Open source, Cross platform (Windows, Linux, Mac), Highly extensible via plugins, Supports many protocols and technologies, CLI and GUI modes, Can be integrated with CI/CD pipelines, Good community support.

On the other hand, Flood.io is a Ai Tools & Services product tagged with load-testing, performance-testing, scalability-testing, cloud-testing.

Its standout features include Record and replay scripts to simulate user journeys, Visual workflow builder to create load tests without coding, Distributed load generation from cloud locations worldwide, Real-time metrics and detailed analytics on test results, Integrations with CI/CD pipelines and external tools, APIs and SDKs to automate and integrate load testing, Ability to simulate millions of concurrent users, and it shines with pros like Intuitive interface and workflows, No need to provision infrastructure, Scales to millions of users easily, Detailed analytics and reporting, Integrates into development workflows, APIs allow for automation and customization.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Apache JMeter

Apache JMeter

Apache JMeter, an open-source tool for performance and load testing of applications. Empower developers and testers to simulate various user scenarios, measure performance metrics, and identify bottlenecks. Apache JMeter supports a wide range of protocols, including HTTP, HTTPS, FTP, SOAP, and more.

Categories:
Development Testing
performance-testing load-testing web-application-testing open-source

Apache JMeter Features

  1. Load testing
  2. Stress testing
  3. Performance benchmarking
  4. Web - HTTP, HTTPS, SOAP, REST, etc
  5. Database via JDBC
  6. FTP
  7. LDAP
  8. Message-oriented middleware (MOM) via JMS
  9. Mail - SMTP(S), POP3(S) and IMAP(S)
  10. Native commands or shell scripts
  11. TCP
  12. Java Objects

Pricing

  • Open Source

Pros

Open source

Cross platform (Windows, Linux, Mac)

Highly extensible via plugins

Supports many protocols and technologies

CLI and GUI modes

Can be integrated with CI/CD pipelines

Good community support

Cons

Steep learning curve

Configuring tests can be complex

GUI has outdated design

Not ideal for mobile app testing

Lacks built-in developer collaboration features

Flood.io

Flood.io

Flood.io is a load testing service that allows users to simulate high traffic loads on their websites and apps to test stability, performance, and scalability. It provides intuitive scripts and visual workflows to build and run load tests from the cloud without requiring complex setup.

Categories:
Ai Tools & Services Website Testing
load-testing performance-testing scalability-testing cloud-testing

Flood.io Features

  1. Record and replay scripts to simulate user journeys
  2. Visual workflow builder to create load tests without coding
  3. Distributed load generation from cloud locations worldwide
  4. Real-time metrics and detailed analytics on test results
  5. Integrations with CI/CD pipelines and external tools
  6. APIs and SDKs to automate and integrate load testing
  7. Ability to simulate millions of concurrent users

Pricing

  • Subscription-Based

Pros

Intuitive interface and workflows

No need to provision infrastructure

Scales to millions of users easily

Detailed analytics and reporting

Integrates into development workflows

APIs allow for automation and customization

Cons

Can get expensive at high loads or long durations

Limited control compared to self-hosted solutions

Scripting for advanced scenarios requires coding

Not ideal for companies with strict data regulations

Reporting less customizable than open source tools