Apache Geode vs. MongoDB

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
MongoDB
Score 8.0 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
Apache GeodeMongoDB
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Apache GeodeMongoDB
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsFully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
Apache GeodeMongoDB
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
Apache GeodeMongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache Geode
8.7
1 Ratings
1% below category average
MongoDB
9.1
38 Ratings
3% above category average
Performance9.01 Ratings9.038 Ratings
Availability10.01 Ratings9.738 Ratings
Concurrency10.01 Ratings8.638 Ratings
Scalability8.01 Ratings9.438 Ratings
Data model flexibility7.01 Ratings9.138 Ratings
Deployment model flexibility8.01 Ratings9.137 Ratings
Security00 Ratings8.638 Ratings
Best Alternatives
Apache GeodeMongoDB
Small Businesses
IBM Cloudant
IBM Cloudant
Score 8.1 out of 10
IBM Cloudant
IBM Cloudant
Score 8.1 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 8.1 out of 10
IBM Cloudant
IBM Cloudant
Score 8.1 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 8.1 out of 10
IBM Cloudant
IBM Cloudant
Score 8.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache GeodeMongoDB
Likelihood to Recommend
7.0
(1 ratings)
9.4
(78 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(67 ratings)
Usability
8.0
(1 ratings)
9.0
(14 ratings)
Availability
-
(0 ratings)
9.0
(1 ratings)
Support Rating
1.0
(1 ratings)
9.6
(13 ratings)
Implementation Rating
-
(0 ratings)
8.4
(2 ratings)
User Testimonials
Apache GeodeMongoDB
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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MongoDB
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
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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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MongoDB
  • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
  • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
  • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
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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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MongoDB
  • An aggregate pipeline can be a bit overwhelming as a newcomer.
  • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
  • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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Likelihood to Renew
Apache
No answers on this topic
MongoDB
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
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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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MongoDB
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
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Support Rating
Apache
Never contacted support
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MongoDB
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
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Implementation Rating
Apache
No answers on this topic
MongoDB
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
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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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MongoDB
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
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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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MongoDB
  • Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
  • You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
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ScreenShots

MongoDB Screenshots

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