TrustRadius
CouchDB is a NoSQL database from Apache.https://dudodiprj2sv7.cloudfront.net/product-logos/zC/x8/4AQBXXWTJLJC.pngCouchDB for analyticsIt'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.,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.,The HTTP content type headers aren't explicitly set to `application/json` when you make a request with your browser. They incorrectly respond with `text/plain`. This issue has been reported multiple times, and even had patches proposed, but so far they've been rejected. CouchDB doesn't support returning gzipped responses. You can get around this by using nginx in front of your CouchDB servers, but it could be faster if it was supported directly. Even in clustered mode, CouchDB nodes aren't able to share computed view data through replication. Each node needs to compute it on their own, which is a little wasteful.,Yes - Master to Master replication and opportunistic concurrency control with revision numbers (rather than locking) make it extremely partition tolerant and help it handle far more concurrent connections than other databases would allow. So long as you understand the conflict resolution model, you will never lose data due to a network partition. It is explicitly made to handle being offline for extended periods of time.,9,Faster development. Since it's a schemaless system, it's easy to add new fields and change the data model, so long as views stay the same. Lower cost of ownership. Unlike paid systems, CouchDB is totally free and supported by the Apache Foundation. The only thing you need to pay for is the hardware it runs on. Easier integration with other services. CouchDB uses a HTTP API for everything, and since nearly all languages have well maintained HTTP libraries, it's easy to connect them to the database.,MongoDB,Docker, Kubernetes, MariaDB,10CouchDB - The Hidden Gem of NoSQL DatabasesDatawhere 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!,Technically easy to use and integrate. REST API allows CouchDB to work with all technologies we use: node.js, lua, python, elasticsearch, logstash, etc. Our experience is that it is very robust and has been trouble-free to sue for over 5 years of heavy daily use. Using map/reduce allows us to quickly implement new views into our customer's data based on their needs. Easy to develop new features based on CouchDB's view/list/show mechanism. Functions are written in Javascript, which allows a broad range of our developer's to understand and contribute to code. NoSQL is wonderful for our data set. We support format-specific metadata for many thousands of different file types without the need to change schemas or anything else. We find that CouchDB allows us to focus more on our applications and customers and less on back-end design. Scales for us well. We have 100's millions of documents, many with binary attachments, stored in thousands of databases. Running on some fairly meager hardware distributed across multiple locations. There is not difference in performance today as when we had a few thousand documents when we started. Replication model is very nice and simple. And fast! We use it for obvious things like backups & redundancy. But we also use it for deploying software updates and for remote data colleciton from customer sites.,CouchDB's documentation is a bit lacking. The technical bits are all there from Apache, but meaningful examples are hard to find. I would say the learning curve is a few months to get fluent. Not that CouchDB is too complex, but it has a design that takes some effort to understand and leverage. But for us the results have been more than worth it. CouchDB could use some better tools for managing & administrating itself. We have many thousands of CouchDB databases and had to invest a bit of development effort to be able to managing it all. But the REST API is simple, there are node.js modules like cradle, etc that minimze any challenges we have had. It is not widely used. Or if it is, not a lot of people are admitting to it! This may be a concern if you are looking for people that have CouchDB experience to work on your project.,CouchDB has a few features that we love and use heavily. The changes API let's us know when something has changed. We use this extensively with logstash to to data reports, extractions, flattening, and exports into things like elasticsearch. Love map/reduce using JavaScript. Not perfect, but nice to be able to jump between node.js and CouchDB in same language. Simple configuration and maintenance. File-based databases, so if you want to move stuff around, you can literally move some files and be done. We looked at most of the NoSQL databases available and did many tests. For us, the simplicity and power of CouchDB made it the best choice we for us 5+ years ago. We have never regretted it nor have we ever considered moving to something else.,10,Biggest impact on our business has been that CouchDB has been pretty invisible from a cost or issues perspective. It just works. We use the Apache releases, so it's free. Of course there is a cost to "free" - we have invested time to become fluent in using and understanding CouchDB. But we feel the investment was well worth the effort and we have a solid, fundamental technology to our products that "just works". There are some things we do - SaaS vs self-hosting - that have probably been kept simple by using CouchDB. Overall, we are extremely happy with CouchDB.,,Elasticsearch, Logstash,10CouchDB has a worse performance than AWS S3It 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.,Can host on your own server Views can do complex things to show subsets of data Install was easy,SUPER SLOW. We do tons of data and S3 and just using the file system were both way faster Using views is too complex Stores entire DB as 1 file, good luck when it becomes many TB,It's effective at being worse than AWS S3 in every way we noticed. But we used for less than a year so it's possible we still needed to understand more about it. Its worst part was that we process tons of data and its performance couldn't match a file system.,2,It wasted our time. It was easier to switch to AWS S3 from couchDB than it was to switch to couchDB from a filesystem so it set us up for that.,Amazon S3 (Simple Storage Service),Laravel PHP Framework, AWS Elastic Beanstalk, PostgreSQL,1CouchDB FanboyIt 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.,Ease of install and setup. Ease of syncing with another database. This was truly set it and forget it. The REST API to read data. No additional drivers are needed to work with CouchDB.,Documentation is always helpful. Took a while to understand how indexing and views worked. User security was a bit hard to set up. Still don't believe we have it correct. It returns data in a non-standard way than we've found with other packages like MongoDB. Caused a few days of head scratching until we realized what we were looking at.,Again the syncing is tremendous and is the core reason we decided to go with CouchDB. We have read a lot of articles about map/reduce, but it is a bit hard to fully understand. This is making searching within the database ineffective.,10,It has saved us hours and hours of coding. It is has taught us a new way to look at things. It has taught us patience as the first few weeks with CouchDB were not pleasant. It was not easy to pick up like MongoDB.,MongoDB,MySQL, Microsoft SQL Server, MongoDB,10Fast and reliable replacement as day to day DB.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.,Faster retrieval is the main key. When the data is denormalized in required format, the response time for queries without id columns are really fast in CouchDB. Replacing Oracle views to bucket structure provides great readability and flexibility to the data. Writing multiple views supporting the needs that will perform the action in an equal amount of time makes CouchDB the favourite database for query-like micro services.,Views need to be more easier for creation. Documentation is the key for the development with multiple languages which this lacks.,8,As a result of using CouchDB as backend for services, we need not worry about failures that often. The response time is the key for the user. Faster response helps serve customers better and reduce the call timings.,Couchbase Server,Jenkins, Bitbucket, JIRA Software
Unspecified
CouchDB
26 Ratings
Score 7.3 out of 101
TRScore

CouchDB Reviews

CouchDB
26 Ratings
Score 7.3 out of 101
Show Filters 
Hide Filters 
Filter 26 vetted CouchDB reviews and ratings
Clear all filters
Overall Rating
Reviewer's Company Size
Last Updated
By Topic
Industry
Department
Experience
Job Type
Role
Reviews (1-8 of 8)
  Vendors can't alter or remove reviews. Here's why.
Sean Lang profile photo
March 31, 2017

User Review: "CouchDB for analytics"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
  • 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.
  • The HTTP content type headers aren't explicitly set to `application/json` when you make a request with your browser. They incorrectly respond with `text/plain`. This issue has been reported multiple times, and even had patches proposed, but so far they've been rejected.
  • CouchDB doesn't support returning gzipped responses. You can get around this by using nginx in front of your CouchDB servers, but it could be faster if it was supported directly.
  • Even in clustered mode, CouchDB nodes aren't able to share computed view data through replication. Each node needs to compute it on their own, which is a little wasteful.
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.
Read Sean Lang's full review
Dave Lundberg profile photo
March 08, 2017

Review: "CouchDB - The Hidden Gem of NoSQL Databases"

Score 10 out of 10
Vetted Review
Verified User
Review Source
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!
  • Technically easy to use and integrate. REST API allows CouchDB to work with all technologies we use: node.js, lua, python, Elasticsearch, Logstash, etc. Our experience is that it is very robust and has been trouble-free to sue for over 5 years of heavy daily use.
  • Using map/reduce allows us to quickly implement new views into our customer's data based on their needs. Easy to develop new features based on CouchDB's view/list/show mechanism. Functions are written in Javascript, which allows a broad range of our developer's to understand and contribute to code.
  • NoSQL is wonderful for our data set. We support format-specific metadata for many thousands of different file types without the need to change schemas or anything else. We find that CouchDB allows us to focus more on our applications and customers and less on back-end design.
  • Scales for us well. We have 100's millions of documents, many with binary attachments, stored in thousands of databases. Running on some fairly meager hardware distributed across multiple locations. There is not difference in performance today as when we had a few thousand documents when we started.
  • Replication model is very nice and simple. And fast! We use it for obvious things like backups & redundancy. But we also use it for deploying software updates and for remote data colleciton from customer sites.
  • CouchDB's documentation is a bit lacking. The technical bits are all there from Apache, but meaningful examples are hard to find. I would say the learning curve is a few months to get fluent. Not that CouchDB is too complex, but it has a design that takes some effort to understand and leverage. But for us the results have been more than worth it.
  • CouchDB could use some better tools for managing & administrating itself. We have many thousands of CouchDB databases and had to invest a bit of development effort to be able to managing it all. But the REST API is simple, there are node.js modules like cradle, etc that minimze any challenges we have had.
  • It is not widely used. Or if it is, not a lot of people are admitting to it! This may be a concern if you are looking for people that have CouchDB experience to work on your project.
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.
Read Dave Lundberg's full review
Josh Stapp profile photo
March 08, 2017

Review: "CouchDB has a worse performance than AWS S3"

Score 2 out of 10
Vetted Review
Verified User
Review Source
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.
  • Can host on your own server
  • Views can do complex things to show subsets of data
  • Install was easy
  • SUPER SLOW. We do tons of data and S3 and just using the file system were both way faster
  • Using views is too complex
  • Stores entire DB as 1 file, good luck when it becomes many TB
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.

Read Josh Stapp's full review
LeVar Berry profile photo
March 08, 2017

User Review: "CouchDB Fanboy"

Score 10 out of 10
Vetted Review
Verified User
Review Source
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.
  • Ease of install and setup.
  • Ease of syncing with another database. This was truly set it and forget it.
  • The REST API to read data. No additional drivers are needed to work with CouchDB.
  • Documentation is always helpful. Took a while to understand how indexing and views worked.
  • User security was a bit hard to set up. Still don't believe we have it correct.
  • It returns data in a non-standard way than we've found with other packages like MongoDB. Caused a few days of head scratching until we realized what we were looking at.
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.
Read LeVar Berry's full review
Aditya Peshave profile photo
December 08, 2016

CouchDB Review: "Fast and reliable replacement as day to day DB."

Score 8 out of 10
Vetted Review
Verified User
Review Source
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.
  • Faster retrieval is the main key. When the data is denormalized in required format, the response time for queries without id columns are really fast in CouchDB.
  • Replacing Oracle views to bucket structure provides great readability and flexibility to the data.
  • Writing multiple views supporting the needs that will perform the action in an equal amount of time makes CouchDB the favourite database for query-like micro services.
  • Views need to be more easier for creation.
  • Documentation is the key for the development with multiple languages which this lacks.
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.
Read Aditya Peshave's full review
Victor Pease Solano profile photo
March 22, 2016

User Review: "CouchDB: NOSQL is faster than SQL"

Score 7 out of 10
Vetted Review
Verified User
Review Source
CouchDB is corporate wide solution used for:

  • route planning for sales force
  • a central farm and mobile devices replicating the content partitioned per user
  • Syncrhonization
  • Fast http interface
  • Dead easy scalability
  • Authentication
  • Security (you must compile your own https capable instance)
  • Project mango is not built in yet
CouchDB is best suited for:
  • db front end for mobile applications
  • apps with no intensive data entry requirements
It is not suited for:
  • bulk operations
  • apps with server side requirements
  • complex queries
Read Victor Pease Solano's full review
No photo available
May 17, 2016

User Review: "CouchDB, our data frenemy"

Score 6 out of 10
Vetted Review
Verified User
Review Source
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.
  • Lightweight NoSQL data store.
  • Can be accessed dynamically using any RESTful-API compliant software.
  • Saves data in documents based on JSON structures.
  • Can view and manipulate data inside your browser.
  • Futon (the in-browser views manager) is not up to par. It lacks tons of needed functionality (like deleting a group of documents in one action).
  • CouchDB is NoSQL, which means accessing data needs views (written in JS only). Your power of accessing data is limited to the power of your written views (so no unified way to access any types of data documents like we see in structures SQL databases).
  • CouchDB software adapters are limited. You mainly have a couch-rest library for rails apps.
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.
Read this authenticated review
No photo available
April 19, 2016

CouchDB Review: "Chillaxin"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
  • Replication sync
  • NoSql schema
  • Small client side implementation (PouchDB)
  • Better client side/mobile implemention
  • Alway room for improvement for documentation
I feel as though CouchDB is a real contender in the NoSQL DB space.
Read this authenticated review

About CouchDB

CouchDB is a NoSQL database from Apache.
Categories:  NoSQL Databases

CouchDB Technical Details

Operating Systems: Unspecified
Mobile Application:No