Apache Geode vs. Azure Cosmos DB

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
Azure Cosmos DB
Score 6.8 out of 10
N/A
Microsoft Azure Cosmos DB is Microsoft's Big Data analysis platform. It is a NoSQL database service and is a replacement for the earlier DocumentDB NoSQL database.N/A
Pricing
Apache GeodeAzure Cosmos DB
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache GeodeAzure Cosmos DB
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 GeodeAzure Cosmos DB
Features
Apache GeodeAzure Cosmos DB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache Geode
8.7
Ratings
2% below category average
Azure Cosmos DB
9.9
Ratings
11% above category average
Performance9.00 Ratings10.00 Ratings
Availability10.00 Ratings10.00 Ratings
Concurrency10.00 Ratings10.00 Ratings
Scalability8.00 Ratings10.00 Ratings
Data model flexibility7.00 Ratings9.00 Ratings
Deployment model flexibility8.00 Ratings10.00 Ratings
Security00 Ratings10.00 Ratings
Best Alternatives
Apache GeodeAzure Cosmos DB
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache GeodeAzure Cosmos DB
Likelihood to Recommend
7.0
(0 ratings)
10.0
(0 ratings)
Likelihood to Renew
-
(0 ratings)
7.6
(0 ratings)
Usability
8.0
(0 ratings)
8.8
(0 ratings)
Support Rating
1.0
(0 ratings)
9.2
(0 ratings)
User Testimonials
Apache GeodeAzure Cosmos DB
Likelihood to Recommend
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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NoSQL platforms are very useful when it comes to security, speed, accuracy, high accessibility with high read and write power. Everything is managed under the cloud and we have the various capabilities of Azure and support for Microsoft products with us. Flexibility in price and variety of features, as well as real-time results, are some of the popular [features] of this platform.
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Pros
  • 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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  • Turn-key geo-redundancy with multi-master writes is unprecedented and unparalleled in the industry!
  • Guaranteed low latency makes Cosmos DB an excellent fit for most of our performance-intensive situations.
  • The tunable consistency model simplifies so many challenges in distributed systems engineering that otherwise require advanced knowledge of computer science topics. I continue to be impressed at how Cosmos DB has abstracted away so much complexity.
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Cons
  • 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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  • When searching by default, it is case sensitive, which must be changed by default
  • In many ways, the price should be more flexible according to the requested facilities, because the price is very expensive for startup companies.
  • It is not fully compatible with most common Streaming Analytics tools applications and developers should be worked on it
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Likelihood to Renew
No answers on this topic
It's efficient, easy to scale, and works. We do have to do a bit of administration, but less now than when we started with this a couple of years ago. Microsoft continues to improve its self-management capability.
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Usability
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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Like I said, Cosmos is the way to go. From all of the services that Azure has, Cosmos is very robust in terms of usability. It's ever-evolving and integrates with other applications seamlessly. The interface is pretty easy to understand. I implemented various solutions for my company and Cosmos was one of them.
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Support Rating
Never contacted support
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The support team is very responsive and we are generally satisfied with Microsoft support, in my opinion support team of a product and service is just as valuable as its quality and performance. Telephone answering, 24-hour hotline, email support and ticketing are excellent.
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Alternatives Considered
Still Experimenting. But looks promising as it has query capabilities over complex data structures
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Azure Cosmos DB for MongoDB is more affordable than many other solutions and works incredibly well if you're within the Azure ecosystem.
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Return on Investment
  • 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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  • Expensive but works if your infra is on Azure data center.
  • No latency and nearly no downtime.
  • Takes time for end users to adapt.
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