

NetApp Cloud Volumes ONTAP and Azure Data Lake Storage compete in the cloud data management and storage category. Azure Data Lake Storage appears to have the upper hand due to its features and ROI.
Features: NetApp Cloud Volumes ONTAP offers robust data protection, efficient storage management, and seamless integration with third-party applications. Azure Data Lake Storage has scalable architecture, advanced analytics capabilities, and comprehensive security features. Users favor Azure's features for their scalability and integration with analytics tools.
Room for Improvement: NetApp Cloud Volumes ONTAP needs better licensing options, more intuitive management, and enhanced reporting capabilities. Azure Data Lake Storage requires improved support documentation, better cost management tools, and faster support responses.
Ease of Deployment and Customer Service: NetApp Cloud Volumes ONTAP is noted for its straightforward deployment processes and responsive customer service. Azure Data Lake Storage is also easy to deploy but receives mixed feedback on support responsiveness. NetApp is considered slightly more user-friendly.
Pricing and ROI: NetApp Cloud Volumes ONTAP has higher setup costs but delivers strong ROI due to performance and customer support. Azure Data Lake Storage is deemed more cost-effective with lower initial costs and substantial ROI driven by advanced features and scalability. User reviews indicate Azure Data Lake Storage provides better overall value.
You can't expect her to know everything about Azure, but she knows who does know, so things can get handled by who knows about the topic the best, and that's usually the best way to handle anything anyway.
A good support experience is marked by the speed of reply and the relevancy of resolution tips.
The support team is very supportive, and most issues are resolved quickly once we get in touch with them.
You can't automatically scale across the world, so for something that requires global scaling, you may have to do more work to get the scalability.
For scalability, I rate Data Lake Storage around eight to nine on a scale of one to ten.
The scalability is limited.
It wouldn't help with outages either; the scaling is manual, and there are no processes we've used to automate that for unexpected scenarios.
Stability is rated around eight to nine out of ten.
I find the stability of Azure Data Lake Storage to be excellent and would rate it as an eight out of ten.
Currently, migration is only one-way possible, and it would be beneficial if this aspect could be improved.
The premium tier, which they recommend for analytics, can't be switched off once enabled. Similarly, if you start on standard tier, you can never upgrade it; you have to delete it and make a new one. These limitations are quite annoying.
With the emergence of AI technology, it would be convenient for storing vector indexes, essential for AI solutions.
My opinion is that support is generally very good. There are instances where they take longer to respond or resolve issues, especially when customers have urgent needs, but ultimately, resolution is achieved.
It would be nice to see technology supporting the Elastic Fabric Adapter on Amazon AWS, therefore getting RDMA technology for more low-latency connections.
Azure Data Lake Storage is cheaper and provides three options for data storage tiers.
The pricing for Data Lake Storage depends on several factors, like the configuration for multiple or single locations and if it uses geo-redundancy storage, which is beneficial but consumes higher costs.
Data Lake Storage can interact with any other Azure resources, providing seamless integration and connectivity.
Allows for automated configuration of data operations such as deletion and transfer between repositories.
It's essentially the blob storage but with more features that are analytics focused because usually that's what people are going to do with the Data Lake, which is ingest data for analytics.
The granular ability to divide up the performance and the amount of storage you want is really fantastic.
| Product | Market Share (%) |
|---|---|
| NetApp Cloud Volumes ONTAP | 7.0% |
| Azure Data Lake Storage | 1.4% |
| Other | 91.6% |

| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 7 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 11 |
| Large Enterprise | 53 |
Azure Data Lake Storage is widely used for data warehousing, storing processed data, raw customer files, and integrating data from multiple sources, supporting analytics, reporting, and machine learning by securely storing JSON, CSV, and other formats.
Organizations use Azure Data Lake Storage to aggregate information for reporting, integrate it into data pipelines, and benefit from secure transfer capabilities. It serves data scientists as a staging area and businesses leverage its Big Data capabilities for developing technological solutions. With strong security features, high scalability, hierarchical namespace for better performance, and efficient data partitioning, it integrates seamlessly with tools like Databricks. Supporting structured, unstructured, and semi-structured data, it is ideally suited for data lakes.
What are the key features of Azure Data Lake Storage?Azure Data Lake Storage finds its application in several industries by enabling technological solutions that leverage its Big Data capabilities. For instance, businesses in finance use it for aggregating financial reports, while retail companies leverage it for customer data analytics. Healthcare industries use it to store and analyze patient data securely. The manufacturing sector benefits by integrating data from different sources to optimize production processes.
NetApp Cloud Volumes ONTAP is an efficient storage management solution for managing and storing data in the cloud. It offers seamless integration with cloud providers, advanced data replication capabilities, and high data protection. With reliable performance, it is ideal for industries like healthcare and finance.
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