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IBM Cloudant

Score7.4 out of 10

123 Reviews and Ratings

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What is IBM Cloudant?

Cloudant is an open source non-relational, distributed database service that requires zero-configuration. It's based on the Apache-backed CouchDB project and the creator of the open source BigCouch project. Cloudant's service provides integrated data management, search, and analytics engine designed for web applications. Cloudant scales your database on the CouchDB framework and provides hosting, administrative tools, analytics and commercial support for CouchDB and BigCouch. Cloudant is often considered part of a new generation of 'NoSQL' databases that don't require fixed table schemas and is challenging the dominance of traditional relational databases (including the popular MySQL).

Top Performing Features

  • Concurrency

    Concurrency is the ability for multiple processes to access or change shared data simultaneously. The greater the number of concurrent user processes that can execute without blocking each other, the greater the concurrency of the database system.

    Category average: 9

  • Data model flexibility

    NoSQL databases do not rely on rely on tables, columns, rows, or schemas to organize and retrieve data, but use use more flexible data models to accommodate the large volume and variety of data being generated by modern applications.

    Category average: 9

  • Performance

    How fast the database performs under data load

    Category average: 9.2

Areas for Improvement

  • Deployment model flexibility

    Can be deployed on-premise or in the cloud.

    Category average: 8.9

  • Availability

    Availability is the probability that the NoSQL database will be available to preform its function when called upon.

    Category average: 8.9

  • Security

    Security features include authentication against external security mechanisms liker LDAP, Windows Active Directory, and authorization or privilege management. Some NoSQL databases also support encryption.

    Category average: 8.9

Outstanding Services and products!!!

Use Cases and Deployment Scope

Software development and cloud storage from IBM

Pros

  • Stay up to date with the ever changing market
  • Fast and reliable
  • Easy to use
  • Great customer service

Cons

  • I think for now it works great I think it can scale further than it already has with the outstanding company IBM is and how much it means to the world as other things with time it should grow!

Return on Investment

  • I think prices are great and fairly priced and that obviously spells good for business!
  • With the other services IBM Cloudant has to offer it makes the investment solid and sound not completely safe but it structures growth in a way that makes it easier for the business to make smarter decisions based on volume.
  • Great product highly recommended!

Happily moved back to cloudant after hosting my own couchdb for a few years.

Use Cases and Deployment Scope

I recommend everyone who evaluated ibm cloudant in the past years since the cloudant aquisition and decided against it due to reliability and maturity of ibm cloud to revisit cloudant. For the last 2 years I can say nothing but positives about the experience and i moved all in-house couchDB and document database hosting to ibm without any issues at all. As a sidenote i was pleasantly surprised by the quality of the fulltext and faceting features of cloudant and even have some workloads handled by cloudant that i previously fullfilled with a separate elastic search installation. This was planned as an intermediate solution but cloudant search worked so well, that it is now a standard part of our solution stack.

Pros

  • sync data with multi master setups and offline capable clients
  • schema-less document storage
  • subscription and reactivity to changing data

Cons

  • ibm cloud billing is still a bit strict and inflexible for some markets and credit card providers, i needed to verify my company and the process could have been nicer.

Return on Investment

  • allowed us to eliminate all internal hosting and move to an edge only architecture

My words on IBM cloudant

Use Cases and Deployment Scope

I used the ibm cloudant database to store the data, actually i want to store the data in nosql and cloudant is a no sql database, So its resoved my data storage issue. We can create n number of collection in a single data base and can access seperately to fulfill the purpose.

Pros

  • Filter by indexing
  • Data storage
  • Nosql

Cons

  • In schema prepration
  • Indexing to filter
  • Tabular view of stored data

Return on Investment

  • Costing is little bit lower as compare to aws
  • Performance is too good
  • Costing as per use is good that can be impact on business objectives.

Alternatives Considered

MongoDB, Amazon DocumentDB (with MongoDB compatibility) and MySQL

Cloudant – I Use It With My Erlang Stack

Use Cases and Deployment Scope

I use Cloudant like I use Couchdb. Each user has a database and I like the ease of use with authentication as well as falling back on Couchdb defaults if wanting to do so. I deal with real-time wait data and use pouchdb to handle my front end.

Pros

  • Ease of use coming from Couchdb - views, indexes, auth, revisions
  • Uptime has been excellent
  • Replication with ease

Cons

  • Better branding - People not used to using IBM services don’t know that Cloudant [was] built around Couchdb.
  • Documentation can be done a bit more organized (some are very old) and do share more of [the] fallback features that Couchdb supplies and what is offered too. I have to sometimes look deep to find out things like fallback auth to use Couchdb auth users for example. Simple stuff.
  • I honestly over time have really no other issues and they aren’t anything extensive since I know Couchdb well.
  • I [have] been happy so far.

Return on Investment

  • Uptime has been great. Only 1 time it went down and I mean AWS has not been perfect all the time.
  • Scalability is amazing.
  • Ease of use again, can jump right in from Couchdb.

IBM Cloudant is the best hosted CouchDB out there

Pros

  • Rapid writes
  • Map reduce
  • High storage capacity
  • High availability

Cons

  • Time to index large databases needs to be improved
  • Could use more structure in terms of separating entities within a database
  • Better pricing on storage sizes as database size increases exponentially

Return on Investment

  • Reduced database design time by as much as 40%
  • Reduced aggregated query run time over terabytes of data by ~30%
  • Reduced write time for a million records in a second by 10%