Databricks Data Intelligence Platform vs. Zoho DataPrep

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

Scenarios where it works well: 1. Preparing reports like CRM, Marketing, and sales for monthly reports. 2. Cleaning CSV files with inconsistent format 3. Removing of duplicates and finding error values 4. Enabling non-technical people to manage data preparation without coding. Scenarios where it is less appropriate: 1. Processing real time data and large scale data needs 2. Deep customization at code level 3. At advanced predictive modeling

Incentivized

• 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

• 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

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

I would rate Zoho DataPrep a 10/10 for its usability because I feel it is very easy and intuitive platform and even non-technical people can access it easily without coding knowledge. Also, its workflow builder is very straightforward, once we create any data pipeline then we can reuse it easily.

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.

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

Zoho DataPrep is much easier to use and quick to set up. It user interface is very user friendly, even people with no technical knowledge can use it easily to transform the data. It creates the repeatable workflows easily and more cost-effective for small to mid-size teams. We selected it because it aligns with our business needs and goals perfectly like fast, easy, and efficient for everyday use.

Incentivized

• 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