Likelihood to Recommend
If you need a managed big data megastore, which has native integration with highly optimized
Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
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Toad Data Point is the clear tool of choice if the end-user is interested in reports that are relatively simple to build using SQL code and export to Excel. It is less useful if the analyst also needs to run statistical models on the data and visualize the data for those functions I usually use
or Jupyter Notebook which incorporates those features much more seamlessly.
Read full review Pros 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 Read full review Ease of building SQL/accessing data, using the Query Builder. The new workflow feature mimics products like Hyperion and is centered on how business analysts are used to working with their data. The dimensional views are definitely a hidden gem. This feature allows you to display similar data in multiple windows, then filter on specifics. ALL windows will then reflect the same data. An example here would be salaries organized by dept then salaries organized by job type. As you filter, both analyses will reflect the filtered data. You can easily create spreadsheets and pivot table spreadsheets. You can email the results to the team/you can save the results in the intelligence central repository so others can access it. You can automate all of these things. Read full review Cons Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code). Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally. Visualization in MLFLOW experiment can be enhanced Read full review The program can error out when reconnecting to a database from a timeout but that is easily fixed by restarting the program. If you aren't familiar with database tools the UI can be overwhelming to some. Read full review Usability
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 Read full review
I find Toad Data Point easy to use for both the novice and the experienced business analyst. If all you desire is to access data and create spreadsheets...this is a snap. Toad Data Point actually has cool data analysis features built into it. The newer workflow interface makes automating steps a snap
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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.
Read full review Alternatives Considered
Databricks has a much better edge than Synapse in hundred different ways. Databricks has Photon engine, faster available release in cloud and databricks does not run on Open source spark version so better optimization, better performance and better agility and all kind of performance boost can be achieved in Databricks rather Open source synapse spark
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Toad give me more flexibility. Being able to utilize FTP to send data and receive files from external systems is wonderful. Using the automation tool to run different database, file, and system activities has made my day-to-day functions easy. Being able to schedule tasks right from the software has also made thing easy.
Read full review Contract Terms and Pricing Model
The problem with this tool and all other ones that are at the top of the industry, it's so expensive that soon as another one will be on the market and deliver the same or different value, it will be catastrophic for them. So you get the fact that they are cashing every dime right now like SAS or Hadoop once did. Now, look at them
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Again, another level of professional services, this is not their biggest strength but this is the cherry on top. I couldn't think about any other professional services like this one. Now I'm talking about meaningful services that really help out our project and delivery.
Read full review Return on Investment 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. Read full review ScreenShots