Apache Geode vs. Couchbase Server

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
Couchbase Server
Score 8.7 out of 10
N/A
Couchbase Server is a cloud-native, distributed database that fuses the strengths of relational databases such as SQL and ACID transactions with JSON flexibility and scale that defines NoSQL. It is available as a service in commercial clouds and supports hybrid and private cloud deployments.N/A
Pricing
Apache GeodeCouchbase Server
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache GeodeCouchbase Server
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Apache GeodeCouchbase Server
Features
Apache GeodeCouchbase Server
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache Geode
8.7
Ratings
2% below category average
Couchbase Server
8.9
Ratings
1% above category average
Performance9.00 Ratings8.90 Ratings
Availability10.00 Ratings9.40 Ratings
Concurrency10.00 Ratings8.90 Ratings
Scalability8.00 Ratings9.40 Ratings
Data model flexibility7.00 Ratings9.00 Ratings
Deployment model flexibility8.00 Ratings8.00 Ratings
Security00 Ratings9.00 Ratings
Best Alternatives
Apache GeodeCouchbase Server
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 GeodeCouchbase Server
Likelihood to Recommend
7.0
(0 ratings)
9.0
(0 ratings)
Likelihood to Renew
-
(0 ratings)
2.1
(0 ratings)
Usability
8.0
(0 ratings)
8.0
(0 ratings)
Availability
-
(0 ratings)
8.0
(0 ratings)
Performance
-
(0 ratings)
9.3
(0 ratings)
Support Rating
1.0
(0 ratings)
8.5
(0 ratings)
Product Scalability
-
(0 ratings)
7.0
(0 ratings)
User Testimonials
Apache GeodeCouchbase Server
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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Best suited when edge devices have interrupted internet connection. And Couchbase provides reliable data transfer. If used for attachment Couchbase has a very poor offering. A hard limit of 20 MB is not okay. They have the best conflict resolution but not so great query language on Couchbase lite.
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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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  • Easy to store unstructured data and has great performance
  • Managing security is super easy which can be managed across different levels
  • UI is pretty simple to use and manage the cluster
  • Backup of the data is very easy and the restoration/recovery is fairly easy as well with the in-built tools.
  • Easy integration with elasticsearch for replication
  • It is fairly easy to scale up or scale down the cluster
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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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  • Cluster sizing during the design phase can be improved, especially if the client lacks prior experience. Vendor consultants are very meticulous in order to provide best of class performance and response time, although some more real-world pragmatic approach is often needed.
  • Couchbase Lite 2 went thru a major revamp, which broke the compatibility of the applications with some features removed and other changed. That needed development teams working to refactor the applications.
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Likelihood to Renew
No answers on this topic
I rarely actually use Couchbase Server, I just stay up-to-date with the features that it provides. However, when the need arises for a NoSQL datastore, then I will strongly consider it as an option
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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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Couchbase has been quite a usable for our implementation. We had similar experience with our previous "trial" implementation, however it was short lived.
Couchbase has so far exceeded expectation. Our implementation team is more confident than ever before.
When we are Live for more than 6 months, I'm hoping to enhance this rating.
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Performance
No answers on this topic
One of Couchbase’s greatest assets is its performance with large datasets. Properly set up with well-sized clusters, it is also highly reliable and scalable. User management could be better though, and security often feels like an afterthought. Couchbase has improved tremendously since we started using it, so I am sure that these issues will be ironed out.
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Support Rating
Never contacted support
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I haven't had many opportunities to request support, I will look forward to better the rating. We have technical development and integration team who reach out directly to TAM at Couchbase.
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Alternatives Considered
Still Experimenting. But looks promising as it has query capabilities over complex data structures
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Couchbase could outperform it's competition considerably for database reads and writes. Full text searches were still faster in Elasticsearch but this is more of a feature than a base platform requirement for us.
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Scalability
No answers on this topic
So far, the way that we mange and upgrade our clusters has be very smooth. It works like a dream when we use it in concert with AWS and their EC2 machines. Having access to powerful instances along side the Couchbase interface is amazing and allows us to do rebalances or maintenance without a worry
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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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  • There have been several areas of our application [that] really needed an ACID compliant database (e.g. strong transactional guarantees) that we thought we could work around while using Couchbase. [In my opinion] that turned out to be a poor bet. You need to be certain that the specific characteristics of a NoSQL database fit your problem.
  • Couchbase does eliminate the need for schema upgrades completely. I.e no downtime or conversion windows as you migrate your data model, adding attributes, etc. This helped with the deployment timeframe associated with DB changes.
  • The database is (apparently) a bit more of a space/memory consumer than originally anticipated. During deployments, we received constant pressure from Couchbase consulting teams to eliminate/reduce the number of indexes, and this was because any mutations to docs in a bucket must check for impact against all indexes. More recent years have started to address this with their "collections" features, which helps isolate indexes to specific sub-groupings of documents.
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