CTERA Edge X Series (discontinued) vs. Databricks Data Intelligence Platform

This is all about the selling you a "Device" and prices vary greatly between resellers. The devices work well, but the pure cloud solutions need a lot of work.

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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• Standard File Backup

• 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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• SQL Backups just don't work reliably. For us, we lost all of our SQL data backed up through the CTERA Application process. Although the logs indicated a success, that was really not the case. This came close to putting us out of business. Luckily I had taken a genuine SQL backup to a folder. Unfortunately it was a month old. We had to pick-up the pieces from there.
• Don't use it for file sync and share. There are better products out there i.e. anchorworks.com
• Support sucks. Good luck with response time and answers that are inconsistent between team members. For example I had to rebuild a VM from scratch. When I re-installed the CTERA client It obviously thought I was adding another device. When I inquired to tech support, one member said "copy the old Data folder" (I still had the old VHD. That did not work). The other directed me to the correct spot to just change the associated folder. The turn-around time was over 24 hours for this simple fix.
• Documentation, plenty of fodder but no real tech there.

• 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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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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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

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.

Unfortunately CTERA does not stack up well if you want a pure cloud BDR. I have use iDrive and Asigra. iDrive has similar support and SQL backup issues. Asigra can vary widely in support and price, but the software is solid.

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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Independently Invited by TrustRadius

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• NONE, it about put us out of business

• 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.

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