Amazon Kinesis vs. Firebase

Perfect for real-time data processing and streaming. Also, there's no need for any specific setup - you just start using it immediately and it easily integrates with the rest of AWS capabilities (like Redshift), although integration with Lambda could be better. You can make your overall analytics landscape way simpler with Kineses even if you have non-Amazon solutions like Tableau. It all integrates really well!

Incentivized

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.

Incentivized

• Integrating with other Amazon services
• Scaling requests
• Totally serverless platform
• Simple management

Incentivized

• Extremely robust. Has about any tool you can think of under one roof making it extremely useful as a backup platform for data analytics or small teams that need something quickly.
• Intuitive and easy UI/UX. Being made and owned by Google, you expect nothing less. Very easy to use for anyone that has any marketing or analytical experience especially in Google Analytics (which I just assume all marketers do).
• Safe, secure, and sturdy. Never need to worry about downtimes or misinformation as it's as clean and safe as it is being run by Google.
• FREE! What else is there to say. Unless you're an extremely large application handling hundreds of thousands to millions of users, this pay as you go plan will stay free.

Incentivized

• Improve integration with AWS Lambda
• Some duplicate records coming from the stream

Incentivized

• Firebase/Firestore has very limited support for querying more complicated items; for example, performing a simple string search is not possible.
• While upfront costs are low, costs can grow quickly if you're not careful about what you are being billed for.
• Dashboards have at times shown different information to what is billed, and support from Google is less than stellar and not as effective as that from Amazon or Microsoft.

Incentivized

Firebase functions are more difficult to use, there are no concepts of triggers or cascading deletes without the use of Firebase functions. Firebase functions can run forever if not written correctly and cause billing nightmares. While this hasn't happened to us specifically it is a thing that happens more than one realizes.

Incentivized

The documentation was confusing and lacked examples. The streams suddenly stopped working with no explanation and there was no information in the logs. All these were more difficult when dealing with enhanced fan-out. In fact, we were about to abort the usage of Kinesis due to a misunderstanding with enhanced fan-out.

Incentivized

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.

Incentivized

Kinesis is oriented to streaming in a scalable way large volumes of information in real-time. Glue is more an ETL so it is not well suited for real-time applications while Beanstalk is more a simple container platform. Lambda could do the job but it would require a lot of programming to accomplish the same as Kinesis. In fact, our solution employed the four elements for different tasks but using Kinesis as the message bus.

Incentivized

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.

Incentivized

• Caused us to need to re-engineer some basic re-try logic
• Caused us to drop some content without knowing it
• Made monitoring much more difficult
• We eventually switched back to SQS because Kinesis is not the same as a Queue system

Incentivized

• Firebase has been able to help us understand reliably, the drop-off in our user flows with their funnel feature. This has made it easy for us to be able to pinpoint weaknesses in our funnel and test and optimize with data as the dependent variable.
• From an economic standpoint, we don't pay for Firebase which is great, but as the saying goes "You get what you pay for" also holds true in this context. As we looked to grow and scale, we looked for a paid solution.
• From a developer resource standpoint, Firebase has been extremely easy to integrate into our app. Whether it be the event tracking, dynamic links or crash reporting we have not had to waste too much developer time thanks to their well-organized developer docs.

Incentivized