Couchbase vs MongoDB

Need advice about which tool to choose?Ask the StackShare community!

Couchbase

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MongoDB

72.9K
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4.1K
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Couchbase vs MongoDB: What are the differences?

Developers describe Couchbase as "Document-Oriented NoSQL Database". Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands. On the other hand, MongoDB is detailed as "The database for giant ideas". MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

Couchbase and MongoDB belong to "Databases" category of the tech stack.

"Flexible data model, easy scalability, extremely fast" is the top reason why over 13 developers like Couchbase, while over 788 developers mention "Document-oriented storage" as the leading cause for choosing MongoDB.

MongoDB is an open source tool with 16.2K GitHub stars and 4.08K GitHub forks. Here's a link to MongoDB's open source repository on GitHub.

According to the StackShare community, MongoDB has a broader approval, being mentioned in 2175 company stacks & 2143 developers stacks; compared to Couchbase, which is listed in 45 company stacks and 20 developer stacks.

Advice on Couchbase and MongoDB
Needs advice
on
MySQLMySQL
and
MongoDBMongoDB

I'm starting to work on a Jira-like bug tracker web app. This is a hobby project that is mostly a way for me to learn about different technologies and development processes(CI/CD, etc..) so I could be more ready when I start applying for programming jobs.

I'm debating between MySQL, which I'm less familiar with, and MongoDB which I have used in the past.

My two points of consideration are the following:

1) Which one is more likely to be relevant for web dev jobs? While I want to learn new technologies, I prefer learning ones that will make me more hireable in the future.

2) Which one is more flexible when it comes to changing the shape of the stored data? I expect to need to make some changes as the project goes on.

Thanks, everyone!

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Replies (2)
Recommends
MySQLMySQL

MySQL is still more popular than MongoDB if you look at Google Trends. I've also added MariaDB, which is pretty much a copy from MySQL and its features, and PostgreSQL, which is also a popular relational database.

This is a very good article for comparing MySQL to MongoDB and which one you should use: MongoDB vs MySQL: A Comparative Study on Databases.

If you just want to learn and you have the time, I would opt for using both MySQL and MongoDB. For example using MySQL for most of the site content and MongoDB for saving log messages. As you get more and more logs you start to see the benefits from MongoDB's faster document fetching.

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Andy Gee
Freelance Developer at DGTEpro · | 4 upvotes · 34.6K views

There's really not an awful lot of difference between the two, they have wildly different storage mechanisms but they each have their fairly similar benefits. If you want to learn something that might be a requisite skill for a job, I would also look at alternatives such as time based and column based systems like InfluxDB and the unbelievably fast and flexible ClickHouse. While they may seem like an unlikely fit for a personal bug tracker app, there's no reason not to use them. Since I got into InfluxDB people have been requesting it a lot and I'll be using ClickHouse for all large databases, probably forever. Expand your horizons beyond your competition's.

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Needs advice
on
MongoDBMongoDB
and
FaunaFauna

I’m doing a school project where I have to design a database for a password manager app like 1Password, bitwarden… I’m not sure which database paradigms I should use. Users would have the ability to create vaults and each vault will have many items and can be sorted into favorite, category, tag list… Please help.

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Replies (1)
Amr Saber
Backend Engineer at Aster · | 6 upvotes · 8.7K views
Recommends
PostgreSQLPostgreSQL

What I have learned through several years of experience, is that by default you should consider SQL database (like PostgreSQL, MySQL, ...) and if does not suit you then you should explore other noSQL options.

SQL is very solid and it can do almost anything and can support almost any kind of systems.

So, for your case I would recommend that you go with SQL. You should start by listing your use cases and infer from them your entities and relations, and work on them in a Top-to-bottom manner, meaning that you should have some entities that are the core dependencies for the other entities. Or, in other words, they can exist without other entities existing, but the opposite is not true, these are your core entities that you should work on first, then gradually build the other entities.

One way to figure out the core entities is to follow how the users will behave in your system, what will the user create first, and what is dependant on other entities.

For example, in your case, on way to do it is to start with the "vault", as everything else cannot exist without it (and it's the first thing a user would create), then do passwords as they depend on the vaults (I would say passwords are "under" the vault), then once you do them, you can start working on tags then categories, and so on...

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I have a project (in production) that a part of it is generating HTML from JSON object normally we use Microsoft SQL Server only as our main database. but when it comes to this part some team members suggest working with a NoSQL database as we are going to handle JSON data for both retrieval and querying. others replied that will add complexity and we will lose SQL Servers' Unit Of Work which will break the Atomic behavior, and they suggest to continue working with SQL Server since it supports working with JSON. If you have practical experience using JSON with SQL Server, kindly share your feedback.

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Replies (2)
TwoBySea

I agree with the advice you have been given to stick with SQL Server. If you are on the latest SQL Server version you can query inside the JSON field. You should set up a test database with a JSON field and try some queries. Once you understand it and can demonstrate it, show it to the other developers that are suggesting MongoDB. Once they see it working with their own eyes they may drop their position of Mongo over SQL. I would only seriously consider MongoDB if there was no other SQL requirements. I wouldn't do both. I'd be all SQL or all Mongo.

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Kevin Deyne
Principal Software Engineer at Accurate Background · | 2 upvotes · 11.5K views
Recommends

I think the key thing to look for is what kind of queries you're expecting to do on that JSON and how stable that data is going to be. (And if you actually need to store the data as JSON; it's generally pretty inexpensive to generate a JSON object)

MongoDB gets rid of the relational aspect of data in favor of data being very fluid in structure.

So if your JSON is going to vary a lot/is unpredictable/will change over time and you need to run queries efficiently like 'records where the field x exists and its value is higher than 3', that's a great use case for MongoDB.

It's hard to solve this in a standard relational model: Indexing on a single column that has wildly different values is pretty much impossible to do efficiently; and pulling out the data in its own columns is hard because it's hard to predict how many columns you'd have or what their datatypes would be. If this sounds like your predicament, 100% go for MongoDB.

If this is always going to be more or less the same JSON and the fields are going to be predictably the same, then the fact that it's JSON doesn't particularly matter much. Your indexes are going to approach it similar to a long string.

If the queried fields are very predictable, you should probably consider storing the fields as separate columns to have better querying capabilities. Ie if you have {"x":1, "y":2}, {"x":5, "y":6}, {"x":9, "y":0} - just make a table with an x and y column and generate the JSON. The CPU hit is worth it compared to the querying capabilities.

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Needs advice
on
MySQLMySQLMongoDBMongoDB
and
FirebaseFirebase

Hey everyone, My users love Microsoft Excel, and so do I. I've been making tools for them in the form of workbooks for years, these tools usually have databases included in the spreadsheets or communicate to free APIs around the web, but now I want to distribute these tools in the form of Excel Add-ins for several reasons.

I want these Add-ins to communicate to a personal server to authorize users, read from my databases, and write to them while they're using their Excel environment. I have never built a website, so what would be a good solution for this, considering I'm new to all of these technologies? I know about the existence of Microsoft Azure, Microsoft SharePoint, and Google Sheets, but I don't know how to feel about those.

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Replies (2)
Recommends
SnowflakeSnowflake

Snowflake is a NoSQL database in the cloud, which also accepts SQL calls. Users can obtain an ODBC driver for SnowFlake, which would allow your Excel apps to write/read from the backend, locally.

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Just definitely don't use firebase. All of MongoDB, MySQL, MariaDB and PostGreSQL have a lot of community support and history.

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Ilias Mentzelos
Software Engineer at Plum Fintech · | 9 upvotes · 65.6K views
Needs advice
on
MongoDBMongoDB
and
CouchbaseCouchbase

Hey, we want to build a referral campaign mechanism that will probably contain millions of records within the next few years. We want fast read access based on IDs or some indexes, and isolation is crucial as some listeners will try to update the same document at the same time. What's your suggestion between Couchbase and MongoDB? Thanks!

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Replies (2)
Jon Clarke
Enterprise Account Exec at ScyllaDB · | 4 upvotes · 40.3K views

I am biased (work for Scylla) but it sounds like a KV/wide column would be better in this use case. Document/schema free/lite DBs data stores are easier to get up and running on but are not as scalable (generally) as NoSQL flavors that require a more rigid data model like ScyllaDB. If your data volumes are going to be 10s of TB and transactions per sec 10s of 1000s (or more), look at Scylla. We have something called lightweight transactions (LWT) that can get you consistency.

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Recommends
MongoDBMongoDB

I have found MongoDB highly consistent and highly available. It suits your needs. We usually trade off partion tolerance fot this. Having said that, I am little biased in recommendation as I haven't had much experience with couchbase on production.

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Needs advice
on
PostgreSQLPostgreSQLMySQLMySQL
and
MongoDBMongoDB

I'm planning to build a freelance marketplace website, using tools like Next.js, Firebase Authentication, Node.js, but I need to know which type of database is suitable with performance and powerful features. I'm trying to figure out what the best stack is for this project. If anyone has advice please, I’d love to hear more details. Thanks.

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Replies (3)
malekmfs
at Meam Software Engineering Group · | 9 upvotes · 87.3K views
Recommends
PostgreSQLPostgreSQL

Postgres and MySQL are very similar, but Mongo has differences in terms of storage type and the CAP theorem. For your requirement, I prefer Postgres (or MySQL) over MongoDB. Mongo gives you no schema which is not always good. on the other hand, it is more common in NodeJS community, so you may find more articles about Node-Mongo stuff. I suggest to stay with RDBMS if possible.

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Recommends
PostgreSQLPostgreSQLMySQLMySQL

This is a little about experience. Postgresql is fine. You can use either the related table structure or the json table structure.

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Ruslan Rayanov
Recommends
MySQLMySQL

We have a ready-made engine for the online exchange and marketplace. To customize it, you only need to know sql. Connecting any database is not a problem. https://falconspace.site/list/solutions

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Dennis Kraaijeveld
Needs advice
on
PostgreSQLPostgreSQLMongoDBMongoDB
and
ExpressJSExpressJS

For learning purposes, I am trying to design a dashboard that displays the total revenue from all connected webshops/marketplaces, displaying incoming orders, total orders, etc.

So I will need to get the data (using Node backend) from the Shopify and marketplace APIs, storing this in the database, and get the data from the back end.

My question is:

What kind of database should I use? Is MongoDB fine for storing this kind of data? Or should I go with a SQL database?

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Replies (3)
Arash JalaliGhalibaf
Software Engineer at Cafe Bazaar · | 10 upvotes · 120.4K views
Recommends
PostgreSQLPostgreSQL

Postgres is a solid database with a promising background. In the relational side of database design, I see Postgres as an absolute; Now the arguments and conflicts come in when talking about NoSQL data types. The truth is jsonb in Postgres is efficient and gives a good performance and storage. In a comparison with MongoDB with the same resources (such as RAM and CPU) with better tools and community, I think you should go for Postgres and use jsonb for some of the data. All in all, don't use a NoSQL database just cause you have the data type matching this tech, have both SQL and NoSQL at the same time.

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Recommends
MongoDBMongoDB

I have found MongoDB easier to work with. Postgres and SQL in general, in my experience, is harder to work with. While Postgres does provide data consistency, MongoDB provides flexibility. I've found the MongoDB ecosystem to be really great with a good community. I've worked with MongoDB in production and it's been great. I really like the aggregation system and using query operators such as $in, $pull, $push.

While my opinion may be unpopular, I have found MongoDB really great for relational data, using aggregations from a code perspective. In general, data types are also more flexible with MongoDB.

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Luciano Bustos
Senior Software Developer · | 1 upvotes · 110.5K views
Recommends
PostgreSQLPostgreSQL

I will use PostgreSQL because you have more powerfull feature for data agregation and views (the raw data from shopify and others could be stored as is) and then use views to produce diff. kind of reports unless you wanna create those aggregations/views in nodejs code. HTH

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Krunal Shah
Full Stack Developer at Infynno Solutions · | 7 upvotes · 128.1K views
Needs advice
on
PostgreSQLPostgreSQL
and
MongoDBMongoDB

I want to store the data retrieved from multiple APIs and perform some analytics on it. The data stored in DB will never/hardly change. First, I thought it would be better to retrieve the data and create table columns for them, but some data might have different columns than others. So I thought about storing the JSON response from API directly to the table and use it. So which database will be the better choice, PostgreSQL or MongoDB.

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Replies (6)
Nikhil Gurnani
Sr. Backend Engineer at Grappus · | 8 upvotes · 120.4K views
Recommends
MongoDBMongoDB

Hey Krunal, your requirement sounds pretty clear and specific to what you want to do with that data. My recommendation to you, would be to use MongoDB. Since schema-less IO is faster in MongoDB, your general speed of reading / writing from and to the database would be quick. Additionally, the aggregate framework is very powerful with large data so that is also something that you can use in computing your analytics.

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Maxim Ryakhovskiy
Recommends
MongooseMongooseMongoDBMongoDB

I suggest you to go with MongoDB, because it is schema-less, i.e., it permits you to easily manipulate the schema of a table. If you want to add a column, it can be done without much effort. Moreover, MongoDB can deal with more types of data, since the latest is stored as key-value pair. I do not what kind of analysis you are going to do, but NoSQL is not the best choice if you are going to use complex queries. In addition, if you are working with huge amount of data and you are interested in optimising the performance, I suggest you PostgreSQL. Since you are speaking about API and JSON, I guess that you may using Node JS for fetching API. I suggest you to try Mongoose, which facilitate the use of MongoDB with Node JS.

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Bob Bass
President & Full Stack Enginee at Narro, LLC · | 3 upvotes · 116.4K views
Recommends
PostgreSQLPostgreSQLMySQLMySQL

This is largely a matter of opinion. I see that someone else responded and recommended MongoDB but since you are doing data analytics, I highly recommend you go with SQL. You're going to have a really hard time normalizing the data when you can't manipulate relationships and bulk edit with a nice update query.

I'm much more experienced with MySQL than any other database and I am having a hard time getting on board with noSQL entirely because it's really hard to query complex data with relationships using noSQL. I'm using Firestore with one of my apps and MongoDB with another app but they both use MySQL for the heavy lifting and then a document database for things like permissions, caching, etc.

It sounds like the type of problem you need to reverse engineer. I'm sure you can imagine what the data sets would look like if you use MongoDB or Postgres. I suspect that putting in a little bit more work up front will pay high dividends and productivity once the data is normalized.

Again - it's largely a matter of preference but I prefer SQL almost every time.

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Tarun Batra
Back End Developer at instabox · | 3 upvotes · 116.6K views

Looks like the use case is to store JSON data. mongoDB and Postgres differ in so many aspects like scaling and consistency. Postgres has excellent JSON support now with the power of SQL. MongoDB is good in handling schema less data. However in this case it seems these differences don’t matter that much. I’d recommend you go with what you are most comfortable with.

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Luiz H. Rapatão
Tech Lead at rapatao.com · | 3 upvotes · 116.5K views
Recommends
MongoDBMongoDB

I don't have an unquestionable opinion regarding your use case. I only trend to pick the MongoDB since it is schemaless avoiding null columns that you not always know when it is used (it depends on the source of the data). The only drawback that I could consider is the query's complexity in MongoDB, sometimes it is a bit tricky, when compared to the traditional SQL queries.

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Recommends
MongoDBMongoDB

MongoDB should be better for unstructured/less structured data.

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Needs advice
on
PostgreSQLPostgreSQL
and
MongoDBMongoDB

I need urgent advice from you all! I am making a web-based food ordering platform which includes 3 different ordering methods (Dine-in using QR code scanning + Take away + Home Delivery) and a table reservation system. We are using React for the front-end, and I need your advice if I should use NestJS or ExpressJS for the backend. And regarding the database, which database should I use, MongoDB or PostgreSQL? Which combination will be better? PS. We want to follow the microservice architecture as scalability, reliability, and usability are the most important Non Functional requirements. Expert advice is needed, please. A load of thanks in advance. Kind Regards, Miqdad

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Replies (3)
Stephen Badger | Vital Beats
Senior DevOps Engineer at Vital Beats · | 9 upvotes · 136.4K views

I can't speak for the NestJS vs ExpressJS discussion, but I can given a viewpoint on databases.

The main thing to consider around database choice, is what "shape" the data will be in, and the kind of read/write patterns you expect of that data. The blog example shows up so much for DBMS like MongoDB, because it showcases what NoSQL / document storage is very scalable and performant in: mostly isolated documents with a few views / ways to order them and filter them. In your case, I can imagine a number of "relations" already, which suggest a more traditional SQL solution would work well: You have restaurants, they have maybe a few menus (regular, gluten-free etc), with menu items in, which have different prices over time (25% discount on christmas food just after christmas, 50% off pizzas on wednesdays). Then there's a whole different set of "relations" for people ordering, like showing them past orders, which need to refer to the restaurant etc, and credit card transaction information for refunds etc. That to me suggests PostgreSQL, which will scale quite well if you database design is okay.

PostgreSQL also offers you some extensions, which are just amazing for your use-case. https://postgis.net/ for example will let you query for restaurants based on location, without the big cost that comes from constantly using something like Google Maps API to work out which restaurants are near to someone ordering. Partitioning and window functions will be great for your own use internally too, like answering questions of "What types of takeways perform the best for us, Italian, Mexican?" or in combination with PostGIS, answering questions like "What kind of takeways do we need to market to, to improve our selection?".

While these things can all be implemented in MongoDB, you tend to lose some of the convenience of ACID or have to deal with things like eventual consistency, which requires more thinking on the part of your engineers. PostgreSQL offers decent (if more complex) scalablity and redundancy solutions, and is honestly very well proven and plenty of documentation exists on optimising queries.

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Anis Zehani
Recommends
MongoDBMongoDB

Hello, i build microservice systems using Angular And Spring (Java) so i can't help with with ur back end choice, BUT, i definitely advice you to use a Nosql database, thus MongoDB of course or even Cassandra if your looking for extreme scalability with zero point of failure. Anyway, Nosql if much more faster then Sql (in your case Postresql DB). All you wanna do with sql can also be done by nosql (not the opposite of course).I also advice you to use docker containers + kubernetes to orchestrate them, if you need scalability and replication, that way your app can support auto scalability (in case ur users number goes high). Best of luck

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Carlos Iglesias
Recommends

About PostgreSQL vs MongoDB: short answer. Both are great. Choose what you like the most. Only if you expect millions of users, I‘ll incline with MongoDB.

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Needs advice
on
MySQLMySQL
and
MongoDBMongoDB

Hello, I am developing a new project with an internal chat between users. Also, there are complex relationships between the other project entities but I wolud like to build something scalable and fast and right now I am designing the data model. What kind of database would you recommend me to manage all application data? relational like MySQL, no relational like MongoDB or a mixed one? Thank you

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Replies (6)
Recommends
PostgreSQLPostgreSQL

In MongoDB, a write operation is atomic on the level of a single document, so it's harder to deal with consistency without transactions.

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Recommends
MongoDBMongoDB

MongoDB supports horizontal scaling through Sharding , distributing data across several machines and facilitating high throughput operations with large sets of data. ... Sharding allows you to add additional instances to increase capacity when required

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Recommends
ArangoDBArangoDB

If you are trying with "complex relationships", give a chance to learn ArangoDB and Graph databases. Its database structures allow doing this with faster and simpler queries. The database is not as strict as others and allows arbitrary data. The data model is really like a neural network and you will never need foreign keys tables anymore. In Udemy there is a free course about it to get started.

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Kit Ruparel
Recommends
Apache AuroraApache Aurora

The most important question is where are you planning to host? On-premise, or in the cloud.

Particularly if you are planning to host in either AWS or Azure, then your first point of call should be the PaaS (Platform as a Service) databases supplied by these vendors, as you will find yourself requiring a lot less effort to support them, much easier Disaster Recovery options, and also, depending on how PAYG the database is that you use, potentially also much cheaper costs than having a dedicated database server.

Your question regards 'Relational or not' is obviously key, and you need to consider both your required data structure, as well as the ACID requirements of your application model, as well as the non-functional requirements in terms of scalability, resilience, whether you want security authorisation at the highest application tier, or right down to 'row' level in the database, etc. - however please don't fall into the trap of considering 'NoSQL' as being single category. MongoDB, with its document-store type solution is a very different model to key-value-pair stores (like AWS DynamoDB), or column stores (like AWS RedShift) or for more complex data relationships, Entity Graph Stores (like AWS Neptune), to stores designed for tokenisation and text search (ElasticSearch) etc.

Also critical in all this is how many items you believe you need to index by. RDBMS/SQL stores are great for having as many indexes as you want, other than the slow-down in write speed, whereas databases like Amazon DynamoDB provide blisteringly fast read/write performance, but are very limited on key indexing capabilities.

It feels like you have most experience with SQL/RDBMS technologies, so for the simplest learning curve, and if your application fits it, then I'd personally start by looking at AWS Aurora https://aws.amazon.com/rds/aurora/ .

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Daniel Mwakanema
Software Developer at Kuunika - Data for Action · | 2 upvotes · 332.3K views
Recommends
MySQLMySQL

FIrstly, it may help if you explain what you mean by "complex relationships between project entities". Secondly, you can build a fast and scalable solution using either. With that said however, the data sounds relational so I would recommend MySQL.

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RODIALSON Tojo
FullStack Developer / CTO at O2Development · | 2 upvotes · 332.6K views
Recommends
MySQLMySQL

I think, Its depend of your project type and your skills. MySQL is good and simple for maintenance but MongoDB need more skills and knowledge. If you work on little project, use MySQL. For your project type, MySQL is enough after you can migrate with PostgreSQL

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Decisions about Couchbase and MongoDB

I’m newbie I was developing a pouchdb and couchdb app cause if the sync. Lots of learning very little code available. I dropped the project cause it consumed my life. Yeats later I’m back into it. I researched other db and came across rethinkdb and mongo for the subscription features. With socketio I should be able to create and similar sync feature. Attempted to use mongo. I attempted to use rethink. Rethink for the win. Super clear l. I had it running in minutes on my local machine and I believe it’s supposed to scale easy. Mongo wasn’t as easy and there free online db is so slow what’s the point. Very easy to find mongo code examples and use rethink code in its place. I wish I went this route years ago. All that corporate google Amazon crap get bent. The reason they have so much power in the world is cause you guys are giving it to them.

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We started using PostgreSQL because there's no need to upgrade to an enterprise plan to access certain essential features. Postgres is essentially plug-and-play; you download it, install it, and there you go!

Another benefit of using Postgres is that you get to use SQL (Structured Query Language)—which isn't for everyone, but I enjoy how flexible and versatile it is.

Postgres also has point-in-time recovery, which you can export wherever you want—This means you can restore data from any given point in time. With this in mind, if you delete something accidentally, you can go back in time and grab said data without restoring the whole database.

Not to mention Postgres is remarkably fast with several thorough benchmarks comparing it to MongoDB, where Postgres mostly came out on top.

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All the benefits of relational joins and constraints, with JSON field types in Postgres to allow for flexibility like mongo. Objection ORM makes query building seamless and abstracts away a lot of complexity of SQL queries.

MongoDB tends to get slow with scale and requires a lot of code to maintain consistency across collections as foreign keys and other constraints are harder to implement. PostgreSQL also has a vibrant community with battle tested stability and horizontal scalability when needed.

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Usman Sadiq
Student at University of Toronto · | 8 upvotes · 60.4K views
Migrated
from
PostgreSQLPostgreSQL
to
MongoDBMongoDB

MongoDB's document-oriented paradigm is nicely suited to the results of our ML model. We felt that this compatibility offered some time savings on figuring out and implementing an extensive data formatting and processing system. MongoDB's flexible schemas schemas (due to it being non-relational) were also attractive as a source of additional agility for our development process. The MongoDB ecosystem also has great GUI tools to simplify testing.

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Sergey Rodovinsky

At Pushnami we were looking at several alternative databases that would support following architectural requirements: - very quick prototyping for an unknown domain - ability to support large amounts of data - native ability to replicate and fail over - full stack approach for Node.js development After careful consideration MongoDB came on top, and 3 years later we are still very happy with that decision. Currently we keep almost 2TB of data in our cluster, and start thinking about sharding.

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Gabriel Pa

After using couchbase for over 4 years, we migrated to MongoDB and that was the best decision ever! I'm very disappointed with Couchbase's technical performance. Even though we received enterprise support and were a listed Couchbase Partner, the experience was horrible. With every contact, the sales team was trying to get me on a $7k+ license for access to features all other open source NoSQL databases get for free.

Here's why you should not use Couchbase

Full-text search Queries The full-text search often returns a different number of results if you run the same query multiple types

N1QL queries Configuring the indexes correctly is next to impossible. It's poorly documented and nobody seems to know what to do, even the Couchbase support engineers have no clue what they are doing.

Community support I posted several problems on the forum and I never once received a useful answer

Enterprise support It's very expensive. $7k+. The team constantly tried to get me to buy even though the community edition wasn't working great

Autonomous Operator It's actually just a poorly configured Kubernetes role that no matter what I did, I couldn't get it to work. The support team was useless. Same lack of documentation. If you do get it to work, you need 6 servers at least to meet their minimum requirements.

Couchbase cloud Typical for Couchbase, the user experience is awful and I could never get it to work.

Minimum requirements The minimum requirements in production are 6 servers. On AWS the calculated monthly cost would be ~$600. We achieved better performance using a $16 MongoDB instance on the Mongo Atlas Cloud

writing queries is a nightmare While N1QL is similar to SQL and it's easier to write because of the familiarity, that isn't entirely true. The "smart index" that Couchbase advertises is not smart at all. Creating an index with 5 fields, and only using 4 of them won't result in Couchbase using the same index, so you have to create a new one.

Couchbase UI The UI that comes with every database deployment is full of bugs, barely functional and the developer experience is poor. When I asked Couchbase about it, they basically said they don't care because real developers use SQL directly from code

Consumes too much RAM Couchbase is shipped with a smaller Memcached instance to handle the in-memory cache. Memcached ends up using 8 GB of RAM for 5000 documents! I'm not kidding! We had less than 5000 docs on a Couchbase instance and less than 20 indexes and RAM consumption was always over 8 GB

Memory allocations are useless I asked the Couchbase team a question: If a bucket has 1 GB allocated, what happens when I have more than 1GB stored? Does it overflow? Does it cache somewhere? Do I get an error? I always received the same answer: If you buy the Couchbase enterprise then we can guide you.

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Omran Jamal
CTO & Co-founder at Bonton Connect · | 4 upvotes · 316.6K views

We actually use both Mongo and SQL databases in production. Mongo excels in both speed and developer friendliness when it comes to geospatial data and queries on the geospatial data, but we also like ACID compliance hence most of our other data (except on-site logs) are stored in a SQL Database (MariaDB for now)

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Kyle Harrison
Web Application Developer at Fortinet · | 11 upvotes · 506.2K views

MySQL has a lot of strengths working for it. It's simple and easy to set up and use. It's JSON engine is also really good these days. Mongo is also simple to setup and use, and it's speed as a document-object storage engine is first class.

Where Postgres has both beat is in it's combining of all of the features that make both MySQL and Mongo great, while adding on enterprise grade level scalability and replication. It's Postgres' stability and robustness, while still fulfilling the roles of it's contemporaries extremely well that edge Postgre for me.

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When I was new with web development, I was using PHP for backend and MySQL for database. But after improving my JS skills, I chosen Node.js. Because of too many reasons including npm, express, community, fast coding and etc. MongoDB is so good for using with Node.js. If your JS skills are enough good, I recommend to migrate to Node.js and MongoDB.

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David Österreicher

Easier scalability of MongoDB prompted this migration from MySQL.

As Runtastic grew, at some point it would have outgrown our MySQL installation. We looked for a couple of alternatives and found MongoDB as a great replacement for our use case. Read how a migration of live data from one database to another worked for us.

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Pros of Couchbase
Pros of MongoDB
  • 18
    High performance
  • 18
    Flexible data model, easy scalability, extremely fast
  • 9
    Mobile app support
  • 7
    You can query it with Ansi-92 SQL
  • 6
    All nodes can be read/write
  • 5
    Open source, community and enterprise editions
  • 5
    Both a key-value store and document (JSON) db
  • 5
    Equal nodes in cluster, allowing fast, flexible changes
  • 4
    Local cache capability
  • 4
    Automatic configuration of sharding
  • 3
    Cross data center replication
  • 3
    Elasticsearch connector
  • 3
    Easy setup
  • 3
    Web based management, query and monitoring panel
  • 3
    Linearly scalable, useful to large number of tps
  • 3
    Easy cluster administration
  • 3
    SDKs in popular programming languages
  • 2
    Map reduce views
  • 2
    DBaaS available
  • 2
    NoSQL
  • 1
    FTS + SQL together
  • 1
    Buckets, Scopes, Collections & Documents
  • 828
    Document-oriented storage
  • 593
    No sql
  • 549
    Ease of use
  • 465
    Fast
  • 408
    High performance
  • 256
    Free
  • 215
    Open source
  • 180
    Flexible
  • 143
    Replication & high availability
  • 110
    Easy to maintain
  • 42
    Querying
  • 38
    Easy scalability
  • 37
    Auto-sharding
  • 36
    High availability
  • 31
    Map/reduce
  • 27
    Document database
  • 25
    Full index support
  • 25
    Easy setup
  • 16
    Reliable
  • 15
    Fast in-place updates
  • 14
    Agile programming, flexible, fast
  • 12
    No database migrations
  • 8
    Easy integration with Node.Js
  • 8
    Enterprise
  • 6
    Enterprise Support
  • 5
    Great NoSQL DB
  • 3
    Drivers support is good
  • 3
    Aggregation Framework
  • 3
    Support for many languages through different drivers
  • 2
    Awesome
  • 2
    Schemaless
  • 2
    Managed service
  • 2
    Fast
  • 2
    Easy to Scale
  • 1
    Consistent
  • 1
    Acid Compliant

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Cons of Couchbase
Cons of MongoDB
  • 3
    Terrible query language
  • 6
    Very slowly for connected models that require joins
  • 3
    Not acid compliant
  • 1
    Proprietary query language

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What is Couchbase?

Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.

What is MongoDB?

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

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Blog Posts

Dec 8 2020 at 5:50PM

DigitalOcean

GitHubMySQLPostgreSQL+11
2
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JavaScriptGitHubNode.js+29
14
12062
GitHubGitDocker+34
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GitHubGitSlack+30
26
16368
What are some alternatives to Couchbase and MongoDB?
CouchDB
Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
HBase
Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
Oracle
Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
See all alternatives