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.
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MongoDB
Score 8.0 out of 10
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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
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Pricing
Couchbase Server
MongoDB
Editions & Modules
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Shared
$0
per month
Serverless
$0.10million reads
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Dedicated
$57
per month
Offerings
Pricing Offerings
Couchbase Server
MongoDB
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
Couchbase's server is more scalable than MongoDB, as MongoDB degrades its performance if the number of users grows. Also, Couchbase allows us to integrate more third-party applications, Couchbase’s query language extends ANSI SQL.
While considering NoSQL database options, we evaluated MongoDB and Couchbase. We decided to go with Couchbase as our dabatase of choice primarily because we had previous Couchbase experience within the team and we knew that this existing expertise could reduce the time needed …
We have good experiences with MongoDB, Elasticsearch, and today we expect to be able to improve our products with
Couchbase and in the near future replace 2 products with 1, which will simplify our product architecture.
The project we are developing with Couchbase, was very inconsistent for few years of the beginning. We had to change data model multiple times. We knew this before starting the project. So we had to choose a NoSQL solution. We also wanted a syncing solution. After some research …
Easy to deploy and manage. Clustering and replication is fairly simple and straightforward. According to developers, Couchbase scored higher points compared to the other products that we evaluated.
Experience with DataStax Cassandra was seamless, but the cost and effort to support it was not justified. Also commercial process experience with Couchbase was much better. ActiveSpaces is a good technology for big TIBCO shop, but keeping with the lifecycle of it is not easy. I …
I'm not qualified enough to make a meaningful comparison, but 2 years after, I hear regularly about issues on Mongo from the other teams, especially on the SRE side. On our side, not much to say, except that it works. Ram, CPU, disk behave like expected. Same for bandwidth. …
Couchbase takes most of the best features of products such as Amazon Aurora, DynamoDB, Mongo DB, or Realm IO. It by the way might be lacking a good AWS strategy compared to other solutions. Couchbase has a great field for improvements in establishing specific deployment …
We looked at several different SQL and NoSQL systems. Most were either too expensive, didn't provide the needed functionality, or were too hard to use with the size of our team. We ultimately went with Couchbase because of its performance, horizontal scalability, and price.
Both Couchbase and MongoDB are document-oriented NoSQL databases, so they have very similar features. While they do have some fundamental differences in terms of how they scale, shard, etc. the one key reason why we went with MongoDB is its availability and support from the …
Cassandra: may be better for bigger use cases, in PB range, due to our use cases being slightly smaller, we did not need this, but we highly rely on efficient indexing, and low latency, which seemed to be better based on our testing in Mongodb. Couchbase Server: Document …
We chose MongoDB because it fit our specific use cases better than the other two NoSQL products that I've identified. There are some use cases where those products would be better. Be sure to use the right tool for the job, for us, it was MongoDB, for you it might not be.