Databricks Data Intelligence Platform vs. Dell PowerScale vs. OpenText Magellan

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.

Incentivized

EMC Isilon Scale-Out NAS is well suited for larger files (greater the 128 Kb) and where you need to have everything in one common name space. Where it is less appropriate is for many small files (millions of files less than 128 Kb in size) - this causes the protection level to becoming mirroring, which will cost more space.

Incentivized

If you do not have a large budget and are a large organization, I would steer clear of Actuate. If you are looking to do very complex washboarding, I would not use them. Your developers have to be very skilled to work with this. Plan to bring in consultants if necessary to help your process. Adhoc reporting is weak. If your pricing is user based and you expand, this could be very expensive.

• 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

Incentivized

• NAS Storage
• Capacity and Performance details of the array
• Alert and Operations details

Incentivized

• The report outputs can vary across different types such as HTML, PDF, and Excel
• Their open source offering is very sufficient
• There are great boards and blogs for developers and engineers to expand and use their features.
• The people from the company that I've worked with are professional and courteous.

Incentivized

• 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.

Incentivized

• Some upgrades require the entire cluster to be rebooted simultaneously. In this day and age, that should not be necessary. This is my biggest disappointment with Isilon to date.
• When using multiple storage pools you have to be very careful with your capacity management. Filling up one pool can cause an overflow of data to a pool that is less performance driven. Do not underestimate your capacities or you will find yourself in a tight spot.
• Block size is almost always an issue with Isilon. It does not handle all types of data well. In many cases PACS and VNA data is best to be stored on a different storage platform that will utilize the capacity more efficiently that Isilon is capable of.
• Deduplication seems to be less efficient on Isilon than on other platforms for similar types of data.

Incentivized

• The documentation on all the available features, but most importantly on the scripting side, can be improved
• The standard look & feel of some basic options, like parameter selection or sorting and filtering, looks dated and can't be customized
• The server portal needs to provide better tools
• More integration is needed with other OpenText products

Incentivized

I am no longer working for the company that was using Actuate but I believe they would continue to use it because the stitching costs would be to high. It would require a complete rewrite of the reports and the never version of Actuate (BIRT) even required an almost complete report rewrite

Incentivized

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

Incentivized

It is quite intuitive to use. It is fit specifically for doing sentiment, emotion, and intention analysis as well as text classification and text summarization. I would have given 10 if it is fit for the purpose of doing image processing and analysis as well. There is a huge market to analyze video and image data.

Incentivized

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.

Always there on the front and backend for us and the client.

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.

Incentivized

Raw disk space vs. logical disk space ratio was significantly better on the Isilon. Fast cache using SSD drives for faster searching is available on the Isilon but not available on the Overland solution. Isilon solution included faster backend switching between nodes.

Incentivized

It is vastly superior to these in many ways, for complex reporting it is a much more sophisticated solution. Visualizations are very good. Javascript extensibility is very powerful, others don't support this or as well. Pentaho and MS are both OLAP oriented. Pentaho is moving more toward big data, which was not our primary focus. Others are stuck in the Crystal Reports Band metaphor.

• 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

• Isilon provides very high value for money
• Matches the performance and storage requirements of the arrays
• EMC provides very skillful and high response team in case of any issues in isilon

Incentivized

• Actuate can handle 50 to 60 sub reports inside a report very well.
• Dynamically creating the datasource, chart, graph, reports are the main advantages. We can do any level of drilling, and can create a performance matrix dashboard efficiently.