IBM Cloudant vs. Riak

IBM Cloudant is the best implementation of CouchDB, or any NoSQL database that you could use if you are looking for a database that can handle extremely rapid writes to a database without having to worry about transactional integrity. IBM Cloudant also abstracts out CouchDB's replication/multi-node requirements and ensures high availability on its own. It also allows map-reduce based indexing which will allow massive databases to be aggregated and queried very quickly. It should not be used in cases where you require structured data which is organized according to a schema, or if you want to maintain ACID database properties.

Incentivized

Riak is very good if you need a resilient data store that can handle large amounts of documents very fast. If you have 1,000,000 documents and need to execute complex queries, it is great. Riak's SOLR engine is fast, however if you have extremely high amount of queries in a very limited time range, it can fail in a bad way.

Incentivized

• We had a small data mart project that required the storage of some rather highly connected data that also had a relatively small footprint. This made IBM Cloudant an obvious choice because we could store the data in a data structure that met our project need al while using a platform that our web development team understood and was comfortable with.
• We had a bunch of geospatial data that we needed for analysis. Having GeoJSON being natively supported by Cloudant made it an easy choice.
• Cloudant was cloud-based and didn't require a DBA support it, this allowed the project to move ahead without pushback from the infrastructure team.

Incentivized

• Reliability -- we rarely have to do anything to maintain our Riak instance. It is just online and available for whatever we throw at it.
• The Riak Python client is an excellent tool and handles parallel writes/reads very well
• There is a large and very receptive community or Riak users and developers who seem to be able to help with most technical questions that have arisen.

Incentivized

• To have a sort of LUW - Logical Unit Work when many documents are involved into a single update process. The changing of one document is related to its status information but it must be synchronized with all the other documents involved in the process.

Incentivized

• Missing a free text search function
• More security work
• Multi-tenant reporting
• More types of index optimised for different structures
• Automating repairs especially after unclean shutdowns
• WebDAV/Samba shares for Riak CS
• Implementing the SQL queries from Riak TS in Riak KV
• Settable replication bandwidth caps
• Safemode start up after failure
• More client integrations

the flexibility of NoSQL allow us to modify and upgrade our apps very fast and in a convenient way. Having the solution hosted by IBM is also giving us the chance to focus on features and the improvement of our apps. It's one thing less to be worried about

Incentivized

Riak works great for our use case but the fact that deletes seem to resurrect is a real issue for us. Unless we can get this solved, we'll continue to look at other products to see if our use case fits. Otherwise Riak is a great product and it fits our use case 95%. We have found work arounds to the remaining 5%.

Incentivized

It's mostly just a straight forward API to a data store. I knock one off for the full text search thing, but I don't need it much anyways. Also, the dashboard UI they give is pretty nice to use. It provides syntax-highlighting for writing views and queries are easy to test. I wish other DBs had a UI like this.

Incentivized

it is a highly available solution in the IBM cloud portfolio and hence we have never had any issues with the data base being available - we also do continuous replication to be on the safer side just in case some thing goes awry. We also perform twice a year disaster recovery tests.

Incentivized

very easy to get started and is very developer friendly given that it uses couchDB analytics. It is a cloud based solution and hence there is no hardware investment in a server and staging the server to get started and the associated delays/bureaucracy involved to get started. Good documentation is also available.

Incentivized

Very happy by the commitment given by the team which has been really good over the last 7 years of usage.

Incentivized

Despite Basho going bankrupt and the project becoming fully open-source, community support is reasonably good, albeit a little slow at times. Paid enterprise-grade support is also available from former Basho engineers but the same company also contributes to the community support for free for basic questions or specific knowledge areas.

online resources are good enough to understand but there is nothing like testing. In our case, we discovered some not documented behavior that we take in count now. Also, the experience in NodeJs is critical. Also, take in count that most of the "good practices" with cloudant are not in online courses but in blogs and pages from independent developers

Incentivized

• Test the architecture on CouchDB helped us to address initial design flaws.
• The migration to Cloudant as such was very painless.
• We have migrate our replication system to Cloudant Android Sync for mobile devices.
• We have regular informal contact with the Cloudant leadership to discuss our use cases and implementation strategies.

Incentivized

MongoDB Atlas and Azure Cosmos DB are the closest competitors we found with Cloudant, especially in terms of fixed pricing and having a GUI for easy viewing and quick edits of data. Cloudant's pricing model flat out beats MongoDB Atlas' in terms of how easy it would be to predict costs. Cosmos DB is a much closer competitor, as it integrates well with Azure's stack similarly to Cloudant and the rest of the IBM Cloud stack; similar [throughout]-based pricing and replication options; and even the GUI and ease of query using SQL, which my team and I were more familiar with. Where Cloudant beats out Cosmos DB is again having a more simple pricing model (ops/sec vs Cosmos' "request units" voodoo) and being based on open-source software assuaging fears of vendor lock-in.

Incentivized

MongoDB seems to have copied a lot of functionality from Riak. This may be because MongoDB hired a number of former Basho engineers when Basho went bankrupt. That said, the new functions added to Riak after it became open source have successfully differentiated itself from MongoDB.

Amazon S3 is a nice tool but when you are at significant scale with regionally specific data (joys of GDPR), it's much easier to keep it in house and Riak CS lets you do exactly that. All you need to do is point your application at Riak CS instead of Amazon S3 and it just works as if nothing has changed.

When we evaluated against Cassandra, we found the tools available did not match our needs at the time.

The service scales incredibly well. As you would expect from CloudDB and IBM combination. The only reason I wouldn't score it a 10 is the fact that document trees can get nested and nested very quickly if you are attempting to do very complex datasets. Which makes your code that much more complex to deal. Its very possible we could find a solution to this problem with better database planning to begin with, but one of the reasons we chose a service over a self-hosted solution was so we could set it up quick and forget about it. So we weren't going to dedicate a team to architecture optimization.

Incentivized

• Saving in-terms of cost of procuring and maintaining hardware, which will be realized over the next 5 years.
• Positive ROI in terms of the number of FTEs involved in maintaining our databases; our DBAs can now focus on other important and business critical applications.
• Best ROI in terms of our organization's vision - they are no longer anxious / nervous to move to the cloud. We are already on the CLOUD.

Incentivized

• Riak's simple API and simple management model made it a no brainer when it came to adopting it as a technology for the team.

Incentivized