Databricks Data Intelligence Platform vs. Workato

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

Workato is brilliant to make separate applications work together without much effort or specialists being needed. When specific events on software A should trigger actions on B (or more) and you want that to happen without any development or big budgets, that's where Workato comes into play. It's a great help if you want tasks automated, communications flowing and data synced between different applications.

• 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

• The Workato product interface is brilliantly thought through and designed. The learning curve for first timers is easy enough to get started and build useful things, and Workato really shines in their ability to handle complex triggers and interactions. Workato allows people to build software apps so much faster than by coding each functionality.
• Workato has fantastic documentation, making things accessible without any holes in the product. The product just works, never has any bugs, never lags, and just generally allows us to see and change exactly what we need to.
• Workato has an absolutely amazing support team. We tried the free version for a while, then realized it was the single most important software tool we have, and we upgraded. The support at the paid tier is A+, seriously the best from any company we've worked with. Feels more like a good friend then a support rep.

• 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

Incentivized

• Customer support - responsive, but often not equipped to help efficiently identify root cause of issue. Need to improve escalation to technical resources and turnaround time
• Recipe organization and sharing. Can be challenging to copy recipes, or grab recipes from publicly available site. There are often dependencies and errors that have vague descriptions.

Incentivized

We need to develop Enterprise Application Integrations and Workato was not designed for this

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

Due to prebuilt recipes, Workato is easy to learn and use for non-technical users if their use case fits the existing recipes. It is not easy for non-technical users to create, modify, debug or maintain complex integrations that are outside the prebuilt recipes.

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.

They employ an extremely knowledgeable team of problem solvers. I've never had a disappointing interaction or one that has left me still searching for answers. I know that when I ask for help, they'll partner with me until we find a solution together

Incentivized

We discovered that we could not use Workato for our more complex, large enterprise integrations. It was useful for simple workflows that matched the prebuilt recipes.

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

We already used Zapier, but since it doesn't support NetSuite we had to choose another automation platform. Now that we've been using Workato for a few months, we have plans to move the stuff we're going through Zapier to Workato. We set up a trial account with all the other platforms, and they were all more expensive and A LOT more complicated than Workato.

• 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

• As business consultants, Workato has greatly improved our offerings to our clients as well as improved the time frame to implement automated workflows and integrations.
• For our clients, the return on investment is almost immediate. Once a Workato recipe is up and running (which can be done very fast), data is integrating, duplicate data entry and user errors are eliminated, and cross-company KPI metrics are easier to report than ever.