Microsoft's Blob Storage system on Azure is designed to make unstructured data available to customers anywhere through REST-based object storage.
$0.01
per GB/per month
IBM watsonx.data
Score 8.8 out of 10
N/A
Watsonx.data is presented as an open, hybrid and governed data store that makes it possible for enterprises to scale analytics and AI with a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and share data.
In Azure, it is the storage to use, and in my view, the Blob Storage offers more, or finer-grained configuration options, than S3. So my recommendation would be to check in detail what is offered. As the Blob Storage is more or less a Microsoft exclusive product, the "interoperability" is more limited than, for example, with S3. The S3 is more widely adopted, and if you cannot exclude a migration scenario from one cloud provider to another, additional effort is needed.
Real-time transaction processing (both reads and writes) is where DataStax Enterprise shines. It's very fast with linear scalability should more resources be needed. Additional nodes are added very easily. DataStax Enterprise on its own (without Solr or Spark enabled) isn't well suited for long complicated reports. The data model doesn't support joining multiple tables together which is common in BI reporting.
Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.
Integration complexity with Security Tools while watsonx.Data is well-suited for native tools, but integration with third-party security tools requires custom connectors or manual ETL pipelines. which leads to an increase in setup time.
As an open source technology Cassandra can be readily used with or without any commercial support. DataStax provides value-added services and features, and in the end it is up to individual situations to strike a balance between the desirability of such support/service versus the associated cost.
Blob storage is fairly simple, with several different options/settings that can be configured. The file explorer has enhanced its usability. Some areas could be improved, such as providing more details or stats on how many times a file has been accessed. It is an obvious choice if you're already using Azure/Entra.
DataStax has a good community built around it and has amazing scalability options. Though the initial setup is a bit costly, in the long run, it makes up for it. It also has powerful monitoring tools and a clean UI.
Microsoft has improved its customer service standpoint over the years. The ability to chat with an issue, get a callback, schedule a call or work with an architecture team(for free) is a huge plus. I can get mentorship and guidance on where to go with my environment without pushy sales tactics. This is very refreshing. Typically support can get me to where I need to be on the first contact, which is also nice.
We have had a few situations where we caused an outage or something has gone wrong and we are able to get a support person to offer live help within minutes. The escalation process is excellent - the best I've seen - and the support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through data model exercises and the subscription I believe still comes with some hours to help get the data model reviewed.
Azure Premium Blob offers better latency than competitors. It works best with the Azure ecosystem, and competitors lack it. Azure Blob even stands out in storage durability, providing up to 16 nines. It can have various use cases that can suit all the organisation's needs. The Azure Blob solution can also be deployed on-premises.
Pinecone and IBM watsonx.data (Milvus in our case) both work great as a full-managed cloud-based vector database. We selected IBM watsonx.data because it integrates well with watson.ai and is a little more beginner friendly than Pinecone, but I think both are great anyway.
