Apache Geode vs. Firebase

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Geode
Score 7.0 out of 10
N/A
Apache Geode is a distributed in-memory database designed to support low latency, high concurrency solutions, available free and open source since 2002. With it, users can build high-speed, data-intensive applications that elastically meet performance requirements. Apache Geode blends techniques for data replication, partitioning and distributed processing.N/A
Firebase
Score 8.2 out of 10
N/A
Google offers the Firebase suite of application development tools, available free or at cost for higher degree of usages, priced flexibly accorded to features needed. The suite includes A/B testing and Crashlytics, Cloud Messaging (FCM) and in-app messaging, cloud storage and NoSQL storage (Cloud Firestore and Firestore Realtime Database), and other features supporting developers with flexible mobile application development.
$0.01
Per Verification
Pricing
Apache GeodeFirebase
Editions & Modules
No answers on this topic
Phone Authentication
$0.01
Per Verification
Stored Data
$0.18
Per GiB
Offerings
Pricing Offerings
Apache GeodeFirebase
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache GeodeFirebase
Features
Apache GeodeFirebase
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache Geode
8.7
1 Ratings
2% above category average
Firebase
-
Ratings
Performance9.01 Ratings00 Ratings
Availability10.01 Ratings00 Ratings
Concurrency10.01 Ratings00 Ratings
Scalability8.01 Ratings00 Ratings
Data model flexibility7.01 Ratings00 Ratings
Deployment model flexibility8.01 Ratings00 Ratings
Best Alternatives
Apache GeodeFirebase
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
AWS Lambda
AWS Lambda
Score 8.3 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloud Private
IBM Cloud Private
Score 9.6 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloud Private
IBM Cloud Private
Score 9.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache GeodeFirebase
Likelihood to Recommend
7.0
(1 ratings)
7.3
(31 ratings)
Usability
8.0
(1 ratings)
7.0
(6 ratings)
Support Rating
1.0
(1 ratings)
7.3
(6 ratings)
User Testimonials
Apache GeodeFirebase
Likelihood to Recommend
Apache
The biggest advantage of using Apache Geode is DB like consistency. So for applications whose data needs to be in-memory, accessible at low latencies and most importantly writes have to be consistent, should use Apache Geode. For our application quite some amount of data is static which we store in MySQL as it can be easily manipulated. But since this data is large R/w from DB becomes expensive. So we started using Redis. Redis does a brilliant job, but with complex data structures and no query like capability, we have to manage it via code. We are experimenting with Apache Geode and it looks promising as now we can query on complex data-structures and get the required data quickly and also updates consistent.
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Google
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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Pros
Apache
  • Super Fast data pull/push
  • Provided ACID transactions, so it works like a SQL Database
  • Provides replication & partitioning, so our data is never lost and extraction is super fast. NoSql like properties
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Google
  • 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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Cons
Apache
  • Needs more supporting languages. Out of box Python, Nodejs adapters would be wonderful
  • Currently it supports just KV Store. But if we could cache documents or timeseries data would be great
  • Needs more community support, documentation.
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Google
  • 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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Usability
Apache
Still Experimenting. Initial results are good. we need to figure out if we can completely replace Redis. Cost wise if it makes sense to keep both or replacement is feasible.
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Google
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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Support Rating
Apache
Never contacted support
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Google
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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Alternatives Considered
Apache
Still Experimenting. But looks promising as it has query capabilities over complex data structures
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Google
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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Return on Investment
Apache
  • Still experimenting so difficult to quote
  • For a small size project/teams might be an overkill as it still has certain learning curve
  • For Medium to large projects with complex Data Structures that need to be queried with a fast o/p it definitely works
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Google
  • 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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