IBM Cloudant vs. Astra DB

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

We use Astra DB to improve our management systems. Storing data has become hassle-free and quite simple. When launching a Cassandra-based cloud application, Astra DB is exactly what you need. In addition to the standard training programs and videos, the extended support and training require significant additional effort to activate and cover which I feel is a bit more tedious task.

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

• We need to be able to process a lot of data (our biggest clients process hundreds of milions of transactions every month). However, it is not only the amount of data, it is also an unpredictable patterns with spikes occuring at different points of time - something athat Astra is great at.
• Our processing needs to be extremaly fast. Some of our clients use our enrichment in a synchronous way, meaning that any delay in processing is holding up the whole transaction lifecycle and can have a major impact on the client. Astra is very fast.
• A close collaboration with GCP makes our life very easy. All of our technology sits in Google Cloud, so having Astra in there makes it a no-brainer solution for us.

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

• Astra DB might be difficult to understand for people who are unfamiliar with Apache Cassandra. Improving the initial experience for newcomers, as well as offering better documentation and lessons, might be advantageous.
• The Astra DB ecosystem may be enhanced by expanding the ecosystem of plugins, integrations, and community-contributed solutions.

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

It's a great product but suffers with counters. This isn't a deal breaker but lets down what is otherwise a good all round solution

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

Their response time is fast, in case you do not contact them during business hours, they give a very good follow-up to your case. They also facilitate video calls if necessary for debugging.

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

We also (briefly) considered building in-house. We wanted to avoid complex "Frankenstein" architectures. Combining Pinecone with another NoSQL datastore like DynamoDB would have increased complexity. A single-managed platform (Astra DB) enabled architectural simplicity and strong reliability, allowing Maester’s development team to prioritize high-value, customer-facing features

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

We are well aware of the Cassandra architecture and familiar with the open source tooling that Datastax provides the industry (K8sSandra / Stargate) to scale Cassandra on Kubernetes.

Having prior knowledge of Cassandra / Kubernetes means we know that under the hood Astra is built on infinitely scalable technologies. We trust that the foundations that Astra is built on will scale so we know Astra will scale.

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

• Database growth planning is less of a concern with Astra, as it scales automatically.
• Currently, they lack fine-grained security at the table level. I suspect that will change over time.
• If your load has peaks and valleys; Astra enables only paying for Reads/Writes; thus you do not need to pay for large servers to support peaks in load.

Incentivized