Firebase vs. IBM DevOps Test Performance

Firebase should be your first choice if your platform is mobile first. Firebase's mobile platform support for client-side applications is second to none, and I cannot think of a comparable cross-platform toolkit. Firebase also integrates well with your server-side solution, meaning that you can plug Firebase into your existing app architecture with minimal effort.

Firebase lags behind on the desktop, however. Although macOS support is rapidly catching up, full Windows support is a glaring omission for most Firebase features. This means that if your platform targets Windows, you will need to implement the client functionality manually using Firebase's web APIs and wrappers, or look for another solution.

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Go for IBM RPT if: 1. You're testing a Java-based Web application with HTTP protocol 2. You wanted to distribute the load across machines easily 3. Your team is in learning phase/not really introduced to a wide range of performance testing tools Do not go for IBM RPT if: 1. You wanted to test REST or any other advanced protocols 2. Your system under test demands a very high user load 3. Your application is written in .NET or any other platform except Java.

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• Analytics wise, retention is extremely important to our app, therefore we take advantage of the cohort analysis to see the impact of our middle funnel (retargeting, push, email) efforts affect the percent of users that come back into the app. Firebase allows us to easily segment these this data and look at a running average based on certain dates.
• When it comes to any mobile app, a deep linking strategy is essential to any apps success. With Firebase's Dynamic Links, we are able to share dynamic links (recognize user device) that are able to redirect to in-app content. These deep links allow users to share other deep-linked content with friends, that also have link preview assets.
• Firebase allows users to effectively track events, funnels, and MAUs. With this simple event tracking feature, users can put organize these events into funnels of their main user flows (e.g., checkout flows, onboarding flows, etc.), and subsequently be able to understand where the drop-off is in the funnel and then prioritize areas of the funnel to fix. Also, MAU is important to be able to tell if you are bringing in new users and what's the active volume for each platform (Android, iOS).

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• Data Parameterisation/ Data Correlation is made simpler compared to its competitors
• Distributed Load Testing is easier to set up
• Performance metric gathering while a test is in progress
• Th look and Feel really helps a beginner to understand and work with.

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• Attribution and specifically multi-touch attribution could be more robust such as Branch or Appsflyer but understand this isn't Firebases bread and butter.
• More parameters. Firebase allows you to track tons of events (believe it's up to 50 or so) but the parameters of the events it only allows you to track 5 which is so messily and unbelievable. So you're able to get good high-level data but if you want to get granular with the events and actions are taken on your app to get real data insight you either have to go with a paid data analytics platform or bring on someone that's an expert in SQL to go through Big Query.
• City-specific data instead of just country-specific data would have been a huge plus as well.

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• Memory utilization could have been improved.(Eats up system's RAM)! It may crash if a test is conducted with the heavy load if adequate RAM is not available in the VM/host machine.
• Licensing could have been made simpler. IBM's licensing method is difficult to follow.
• Support for protocols other than HTTP. Not really up to the current trend.

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I don't use the Firebase UI much, but rather connect it to GA4. GA4 has a great event model but the GA4 UI and analysis capabilities are limited. It's harder to measure product usage type of engagement but if you have the time and resources to leverage the GA4 to BiqQuery export you'll have all the raw event data you'll need for deep analysis, segmentation, and audience activation.

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Our analytics folks handled the majority of the communication when it came to customer service, but as far as I was aware, the support we got was pretty good. When we had an issue, we were able to reach out and get support in a timely fashion. Firebase was easy to reach and reasonably available to assist when needed.

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Before using Firebase, we exclusively used self hosted database services. Using Firebase has allowed us to reduce reliance on single points of failure and systems that are difficult to scale. Additionally, Firebase is much easier to set up and use than any sort of self hosted database. This simplicity has allowed us to try features that we might not have based on the amount of work they required in the past.

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Cost/Licensing: While JMeter is an opensource testing tool from Apache, compared to IBM RPT and HP LoadRunner, RPT is much cheaper than Loadrunner. Functionality: JMeter provides basic functionalities which are adequate for performance testing, however advanced features are not available (such as load testing with GUI, reporting is very basic etc.). But when it comes to Loadrunner, it offers very broad features and supports a variety of protocols. So in this category, Loadrunner is a winner, but RPT is better than JMeter. Ease of operating: JMeter is easy compared to LoadRunner, but it has old GUI and look and feel is not that great to understand. Also, most of the things are to be done in a command line, non-GUI mode. While LoadRunner is very advanced with many options, which also confusing sometimes. But RPT, on the other hand, maintains a balance between simplicity and offering of different features. So winner: RPT.

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• Makes building real-time interfaces easy to do at scale with no backend involvement.
• Very low pricing for small companies and green-fields projects.
• Lack of support for more complicated queries needs to be managed by users and often forces strange architecture choices for data to enable it to be easily accessed.

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• Accuracy in metrics, thus improving system's performance
• Costs less compared to competitor like HP LoadRunner
• Helped the team of beginners learn things quickly

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info