IBM Cloudant vs. Neo4j

Our organization found Cloudant most suitable if One, a fixed pricing structure would make the most sense, for example in a situation where the project Cloudant is being used in makes its revenue in procurement or fixed retainer — thus the predictability of costs is paramount; Two, where you need to frequently edit the data and/or share access to the query engine to non-engineers — this is where the GUI shines.

Incentivized

Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using Tableau, for example.

Incentivized

• For us, performance and scalability is the key, and Cloudant DB backed by CouchDB is scalable and performant.
• IBM Cloudant dB is very easy to provision for sandbox, development, QA as well as production.
• Support for Java for CouchDB app server analytics enables a greater control for over developers.
• Schema free oriented very easy to program and build applications on it.
• We love it!!

Incentivized

• Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios.
• Native support for REST API, that makes interacting with Neo4J intuitive and easy.
• Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language.
• Nice UI and interface for executing the Query and visualizing the response.
• UI access controlled by User credentials allows for neat access controls.
• Awesome free community edition for small-scale projects.

Incentivized

• It was only after we went with the cloud-based solution that IBM rolled out an on-premise version.
• We found that a 3rd-party ODBC driver was required for a few applications that needed to pull data out of Cloudant.
• The sales process was difficult because the salesperson we used was not as versed on Cloudant as I had hoped.

Incentivized

• One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution.
• Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API.
• There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software.

Incentivized

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'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

[Based on] Query Language, Performance on small and large data sets, integration and deployment, analysis, API support, Interactive UI.

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

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

The feature-set, including security, is very comparable. Overall, IBM's services added to the product are mature and stable, although product support and engineers could be a little better. Global availability is improving, and Disaster Recover Capabilities are great. Overall, it's very comparable to MongoDB as a DBaaS offer, available globally and with great documentation.

Incentivized

Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive. MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to MongoDB yet, whereas Neo4J is ACID complaint with all its operations.

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

• IBM Cloudant is very secure and we never have to worry about losing data/unauthorized access
• It is one of the best data backup system and works well
• Global availability means it is easy to connect to the nearest data center and this reduces load time which is great.

• Positive: Less complex queries on graph structures, than in relational databases.
• Negative: maintenance is a huge deal, things doesn't work and break, requiring lengthy restore operations.