Apache CouchDB is an HTTP + JSON document database with Map Reduce views and bi-directional replication. The Couch Replication Protocol is implemented in a variety of projects and products that span computing environments from globally distributed server-clusters, over mobile phones to web browsers.
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Azure Blob Storage
Score 9.0 out of 10
N/A
Microsoft's Blob Storage system on Azure is designed to make unstructured data available to customers anywhere through REST-based object storage.
$0.01
per GB/per month
MongoDB
Score 8.9 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 CouchDB
Azure Blob Storage
MongoDB
Editions & Modules
No answers on this topic
Block Blobs
$0.0081
per GB/per month
Azure Data Lake Storage
$0.0081
per GB/per month
Files
$0.058
per GB/per month
Managed Discs
$1.54
per month
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
CouchDB
Azure Blob Storage
MongoDB
Free Trial
No
Yes
Yes
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
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Community Pulse
Apache CouchDB
Azure Blob Storage
MongoDB
Considered Multiple Products
CouchDB
Verified User
Engineer
Chose Apache CouchDB
I have briefly used MongoDB in other products, and it proved that it had better integration capabilities with Ruby on Rails and node.js software platforms, more than CouchDB. But I never had the chance to actually replace CouchDB with MongoDB in the current product to see what …
We looked at MongoDB and Firebase. MongoDB gives us the best working db engine with a very intuitive design. However, it does not work as well offline. Firebase was extremely hard to create searching and indexing. Using a third-party to search didn't work for us or at least it …
MongoDB and CouchDB are both document stores, but their concurrency models and ability to scale are very different. MongoDB cannot replicate / shard over unreliable links and network partitions have been the cause of data loss in the past. MongoDB has an easier query language …
Compared to MongoDB, CouchDB's Map-Reduce paradigm poses a steeper learning curve for SQL users. However, CouchDB's master-master replication is an advantage of implementing a load-balanced solution. Even though, currently, CouchDB has strong community support, as an open …
It has been 5+ years since we chose CouchDB. We looked an MongoDB, Cassandra, and probably some others. At the end of the day, the performance, power potential, and simplicity of CouchDB made it a simple choice for our needs. No one should use just because we did. As I said …
MongoDB is probably the most famous NoSQL database of the moment. it has become one of the most promising startups. Some companies that currently use MongoDB are Foursquare or eBay. This type of database is designed to perform queries and aggregations on large amounts of data. …
MongoDB was the most full-featured NoSQL database we evaluated - that offered atomic transactions at a document level, built-in HA & DR, open source, robust queries, and enterprise level support.
Other platforms had specific parts of what we were looking for - MongoDB had it all.
MySQL is a great for querying related data, but it's unable to store structured data and has a fixed schema. Also SQL can be non-intuitive. DynamoDB, CouchDB and Redis all make querying the data quite difficult and lack important features. The problem CouchDB tries to solve is …
MongoDB provides better performance on a big database. If you prefer to define indexes rather than a map/reduce function, MongoDB is good for you. It's quick to start it up and very easy to learn, basically no entry barrier. MongoDB's community is very welcoming.
Great for REST API development, if you want a small, fast server that will send and receive JSON structures, CouchDB is hard to beat. Not great for enterprise-level relational database querying (no kidding). While by definition, document-oriented databases are not relational, porting or migrating from relational, and using CouchDB as a backend is probably not a wise move as it's reliable, but It may not always be highly available.
In Azure, it is the storage to use, and in my view, the Blob Storage offers more, or finer-grained configuration options, than S3. So my recommendation would be to check in detail what is offered. As the Blob Storage is more or less a Microsoft exclusive product, the "interoperability" is more limited than, for example, with S3. The S3 is more widely adopted, and if you cannot exclude a migration scenario from one cloud provider to another, additional effort is needed.
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.
It can replicate and sync with web browsers via PouchDB. This lets you keep a synced copy of your database on the client-side, which offers much faster data access than continuous HTTP requests would allow, and enables offline usage.
Simple Map/Reduce support. The M/R system lets you process terabytes of documents in parallel, save the results, and only need to reprocess documents that have changed on subsequent updates. While not as powerful as Hadoop, it is an easy to use query system that's hard to screw up.
Sharding and Clustering support. As of CouchDB 2.0, it supports clustering and sharding of documents between instances without needing a load balancer to determine where requests should go.
Master to Master replication lets you clone, continuously backup, and listen for changes through the replication protocol, even over unreliable WAN links.
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.
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.
Because our current solution S3 is working great and CouchDB was a nightmare. The worst is that at first, it seemed fine until we filled it with tons of data and then started to create views and actually delete.
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.
Couchdb is very simple to use and the features are also reduced but well implemented. In order to use it the way its designed, the ui is adequate and easy. Of course, there are some other task that can't be performed through the admin ui but the minimalistic design allows you to use external libraries to develop custom scripts
Blob storage is fairly simple, with several different options/settings that can be configured. The file explorer has enhanced its usability. Some areas could be improved, such as providing more details or stats on how many times a file has been accessed. It is an obvious choice if you're already using Azure/Entra.
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.
Microsoft has improved its customer service standpoint over the years. The ability to chat with an issue, get a callback, schedule a call or work with an architecture team(for free) is a huge plus. I can get mentorship and guidance on where to go with my environment without pushy sales tactics. This is very refreshing. Typically support can get me to where I need to be on the first contact, which is also nice.
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.
it support is minimal also hw requirements. Also for development, we can have databases replicated everywhere and the replication is automagical. once you set up the security and the rules for replication, you are ready to go. The absence of a model let you build your app the way you want it
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.
Azure Premium Blob offers better latency than competitors. It works best with the Azure ecosystem, and competitors lack it. Azure Blob even stands out in storage durability, providing up to 16 nines. It can have various use cases that can suit all the organisation's needs. The Azure Blob solution can also be deployed on-premises.
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.
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