Databricks Data Intelligence Platform vs. Scality ARTESCA

Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.

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The team in charge of implementing Scality has to be full stack in order to guarantee the correct functioning of the entire system. However, you have to think very carefully about the balance between servers and disks, perhaps adopting smaller fully populated servers instead of large semi-populated servers, which would mean that over time our disk updates will not have a fully useful life.

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• Process raw data in One Lake (S3) env to relational tables and views
• Share notebooks with our business analysts so that they can use the queries and generate value out of the data
• Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
• Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers

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• I love the redundancy of the software.

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• Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
• It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
• For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.

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• The overall packaging is not very good. I think it could be more efficient for installation.
• There are many components in storage servers. This can generally be complex to understand, you have to be patient.

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Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX

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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.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.

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

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The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.

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Due to the nature of our business we require extensive encryption and availability for sensitive customer data. The erasure encoding that Scality provides gives us the assurance that documents are rest are never in a state of being downloaded or available to a casual data thief. This is something that can be found with other vendors but at a fraction of the same cost. Having this kind of performance, availability and redundancy at the cost that Scality provides has made a large difference to our organization.

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• The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
• DB has the ability to terminate/time out instances which helps manage cost.
• The ability to quickly access typical hard to build data scenarios easily is a strength.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Keeping sensitive customer data secure is a must for our organization and Scality has great features to make this happen.
• We replaced a single SAN with a Scality ring and found performance to improve as we store more and more customer data.
• Being able to lose various portions of our Scality ring and allow it to continue to service customers while maintaining high performance has been key to our business.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info