Azure Data Lake Storage vs. Scality ARTESCA

Azure Data Lake storage is well suited for applications/use cases within organizations where capturing and storing large amounts of data in any format is required, primarily for storing and processing purposes. It's an easy and cost-effective cloud solution for your application data. The ability to integrate with other Azure Services like Azure Databricks and Azure Data Factory is superb.

Incentivized

When high availability and keeping sensitive information safe are top priority Scality is a great option and has good features that make it ideal for these type of applications. For small companies with limited resources to administer extensive systems Scality would not be a good match. It takes people dedicated to this platform to keep it functioning at its best.

Incentivized

• Azure Data Lake Storage is extremely scalable. It allows us to scale up or down endlessly based on what we need including replication.
• In terms of security, Azure Data Lake Storage fits our requirements really well as we can monitor and encrypt seamlessly. We can also assign permissions through roles and grant network-level access.
• Due to the fact that it can scale, we are able to monitor the cost of storage and any given time and make financial decisions about our infrastructure based on how small or big we want to scale.

Incentivized

• It has a good evolutionary trend to stay alongside AWS as a leader.
• The web-based Supervisor GUI and Grafana statistics allow you to drill down into historical data in many ways.
• Easy for the end user to use.
• The system works so well that we now use it for scalable file system storage and disk-to-disk backups.

Incentivized

• I'd like to see a better cross-platform native client. Azure Data Explorer is fine, but it's far from the "SSMS" kind of experience SQL Server users are used to.
• Listing a large number of file is somewhat problematic and slow. Using the native C# library, running directly on an Azure VM, it can take several hours to list just a couple million files.
• Switching from V1 to V2 requires the creation of a new Storage Account and that's pretty inconvenient.

Incentivized

• From my limited experience, I have not seen anything that needs to be improved. I have found the product to be easy to use.

Incentivized

As an organization, it took us a while to understand the shift from a traditional black box SAN to software-defined storage, but now we are much more certain of what this means. The time invested and the resources were not very high, thanks on the one hand to the technical support and on the other to the coherence and good development of the platform.

Incentivized

I have seen Scality in the office meeting with our VP and get the feeling that they are here to support us.

Incentivized

The Azure Data Lake solution is designed for organizations that want to take advantage of big data. It provides a data platform that can help developers, data scientists, and analysts store data of any size and format and perform all types of processing and analytics across multiple platforms and programming languages. It can work with your existing solutions, such as identity management and security solutions. It also integrates with other data warehouses and cloud environments. It can be useful for organizations that need the above softwares.

Incentivized

In reality, it did not become a substitute for AWS, since it allowed us to maintain a much more compact and rigid system by taking advantage of the support and evolutionary trend that Scality has and keeping AWS as a leader.

Incentivized

• The cost can be high for more advanced work. In some cases, for instance, time limits and lab runtimes may be too short if you are too slow to learn what is explained as you go along.
• promote flexible team communication. You can create different spaces for different teams, and share files and tasks.

Incentivized

• We have had a positive ROI.

Incentivized