IBM Cloudant vs. Google Cloud SQL

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

Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.

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

• Very easy to use and migrate existing database systems to Google Cloud SQL system
• Easy to query with real-time query assessment as well as processing metrics to help optimize the queries
• No need to learn any other querying language (like in Hadoop ecosystem), as SQL works pretty fine
• Easy-to-use GCP portal to type in queries and see the results on the screen (no need to go on command line )
• Easy to set up

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

• Increasing support for more database engines may enable a wider range of application needs to be met.
• Implementing and updating cutting-edge security features on a constant basis.
• Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.

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

It fits the current needs and bandwith of out lean organization.

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

As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.

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

GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.

Incentivized

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

Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.

Incentivized

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

• The first one is it's performance is very good and it comes up with different solution.
• Security can be improved for external resources or the schemas which are selected in it.
• It can be more fragile so one can use it in the business purposes and this will make it a great product.

Incentivized