Apache CouchDB Reviews and Ratings

Use Cases and Deployment Scope

CouchDB fulfills a nice problem for us: we use it to store time-series data for a test sensor network, and it is a great introduction to non-SQL concepts and technologies. After performing feasibility analysis on a few projects looking for a good, solid no-SQL solution, several platforms were examined, including MongoDB. However, for this particular project, MongoDB was simply too large for the Job, and no one on the staff had much experience with non-SQL DBMS's. So, we needed a small, powerful database that worked out of the box, and was easy to understand and therefore implement. The value proposition of CouchDB is its simplicity: It's easy to setup and configure and therefore easy to delegate to an IT analyst, and not worry about blowing project funds on hiring outside talent (usually). The Second proposition of CouchDB is that it is developer friendly: you don't need a salesman from XYZ, Corp. to pitch your development team(s) multi-grand licensing deals just to get it up and running: it's open source and works on all of the big platforms (i.e. OSes).

Likelihood to Recommend

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.

Use Cases and Deployment Scope

Currently, we use CouchDB in various projects throughout our Big Data Insight Product Division for development and production environment setup. Mainly it is being used to store serialized (JSON formatted) unstructured data. For our development environment, usually, a single node DB is more than sufficient for prototyping and to deliver Minimum Viable Product (MVP). However, for production setup, which demands High Availability (HA), a cluster DB with replication capability is a must.

Likelihood to Recommend

CouchDB is particularly suitable for storing unstructured or semi-structured data that does not require strict fields and data types. JSON document with RESTful HTTP API for operation is highly desirable to be stored as a serialized object for Web and Mobile applications. However, NoSQL and Map-Reduce paradigm might be a significant hurdle to integrate with SQL-RDBMS system.

Use Cases and Deployment Scope

It's being used as a document store for a social media analytics system, dumping thousands of updates an hour into a map/reduce system that generates reports and feeds into other task-specific databases. It's a more flexible alternative to relational databases like MySQL, and is easier to scale due to master-master replication.

Likelihood to Recommend

It's good as a general JSON document store and basic map/reduce system. For more specialized tasks like message queuing, graph traversal, streaming metrics aggregation, or arbitrary table joins, I'd recommend another database.

Use Cases and Deployment Scope

Datawhere provides a file intelligence platform that helps people and companies find digital assets ("file") across platforms, devices, and geographic barriers. Our customers are mostly in media-oriented companies - advertising, film, visual effects, post-production, etc., - that have large numbers of distributed, rapidly changing file sets that are touched by many users.

We use CouchDB + Logstash + Elasticsearch to provide incredibly fast, powerful "search and do stuff" functionality for our customers. And they love it!

Likelihood to Recommend

We have a read-heavy environment and CouchDB excels for us. We also use elasticsearch with CouchDB for powerful and fast searching. We also have both SaaS and self-hosted deployments of our technology. CouchDB has been great to use on our infrastructure, as well as on our customer's systems. Simple to deploy, virtually no management. Scales to all sorts of hardware (we have it on Raspberry PIs!).

Do your homework and understand the nature of your data and how it needs to be stored, accessed, and moved around. Make sure that NoSQL fits your problem. If it does, look at CouchDB. It isn't the most popular NoSQL database, but we love it.

Use Cases and Deployment Scope

It held a million SERP pages gathered each day. That information was then parsed to find ads on each page. Building the views and actually deleting files with a compact took ages. On a large AWS server, it took about a day to delete information for one day which has to happen every 6 months. We replaced CouchDB a year ago with AWS S3 and S3 has been amazing. We keep track of the metadata to pull S3 files in our own data base.

Likelihood to Recommend

If you want to do more than just storing files on the server, need to share them over the net and not use S3 then couchDB might work out. If you need something with performance and are writing 100GB daily, CouchDB is gonna have a hard time, particularly when you want to start actually deleting with compact rather than their delete that just soft deletes.

Use Cases and Deployment Scope

It is being used within all the mobile applications we develop where offline data is needed. The ability for CouchDB to sync is truly amazing and saved us lots of headaches and heartache.

Likelihood to Recommend

Mobile and social medial style applications are the best for this style of database. It would be a bit harder to use it in places that are search heavy.

Use Cases and Deployment Scope

There are multiple legacy applications which use SQL databases as a backend for services which are invoked from POS systems. We managed to migrate these applications to CouchDB which provided a faster response.

Likelihood to Recommend

Well Suited: Services/applications that return or act as a backend to the application that require a fast throughput.

Less Appropriate: Data structure is too complex to do denormalization and will require multiple hops to serve one request.

Use Cases and Deployment Scope

I am using CouchDB as the main NoSQL information database server for our product, a globally used network testing and security product. CouchDB helps us save and access thousands of documents of crucial information representing the data points and meta data of the product activities.

Likelihood to Recommend

I can say that generally if your application is in need for a data store where you care more about dumping data than extracting and viewing it, use CouchDB. It's fast. However, you should know that if your data grows really big, reindexing slows down everything. And I can recall many scenarios when reindexing took the database down for a few minutes after every production deploy, that we had to take the website down for a few minutes reporting to our clients temporary unavailability of service (which was expected after a major upgrade).

If your product depends heavily of mining data, stay away from CouchDB, since it's not the best out there when it comes to data search capabilities. May be then it's worth more looking into other options like MongoDB.

Use Cases and Deployment Scope

CouchDB was used for data replication across different audiences and when users were in offline mode (no/low internet). It was initially used as a proof of concept with an intent to use across mobile apps.

Likelihood to Recommend

I feel as though CouchDB is a real contender in the NoSQL DB space.

Use Cases and Deployment Scope

CouchDB is corporate wide solution used for:

<ul><li>route planning for sales force</li><li>a central farm and mobile devices replicating the content partitioned per user</li></ul>

Likelihood to Recommend

CouchDB is best suited for:

<ul><li>db front end for mobile applications</li><li>apps with no intensive data entry requirements</li></ul>It is not suited for:

<ul><li>bulk operations</li><li>apps with server side requirements</li><li>complex queries</li></ul>