jKool vs. StreamSets DataOps Platform

JKool is a decent tool for retrieving information regarding user engagement and customer feedback for your software products. With these information it's very valuable stepping stone for us to make future updates or produce new products. However, there are some downsides with jKool, two of which are there are too much clutter in the GUI and it takes sometimes to turn how things work.

Incentivized

Majorly for all Batch and Streaming Scenarios we are designing StreamSets pipelines, few best suited and tried out use cases below : 1. JDBC to ADLS data transfer based on source refresh frequency. 2. Kafka to GCS. 3. Kafka to Azure Event. 4. Hub HDFS to ADLS data transfer. 5. Schema generation to generate Avro. The easy to design Canvas, Scheduling Jobs, Fragment creation and utilization, an inbuilt wide range of Stage availability makes it an even more favorable tool for me to design data engineering pipelines.

Incentivized

• A easy to use canvas to create Data Engineering Pipeline.
• A wide range of available Stages ie. Sources, Processors, Executors, and Destinations.
• Supports both Batch and Streaming Pipelines.
• Scheduling is way easier than cron.
• Integration with Key-Vaults for Secrets Fetching.

Incentivized

• Monitoring/Visualization can be improvised and enhanced a lot (e.g. to monitor a Job to see what happened 7 days back with data transfer).
• The logging mechanism can be simplified (Logs can be filtered with "ERROR", "DEBUG", "ALL" etc but still takes some time to get familiar for understanding).
• Auto Scalability for heavy load transfer (Taking much time for >5 million record transfer from JDBC to ADLS destination in Avro file transfer).
• There should be a concept of creating Global variables which is missing.

Incentivized

No other product that I used is similar to jKool, it's unique product that have good amount of features that I would be opened to invest more in the future if time permit. It still has a long way to go and the first thing it can do is clean up it user interface to make it better.

Incentivized

StreamSets is a one-stop solution to design Data engineering Pipelines and doesn't require deep Programming knowledge, It's so user-friendly that anyone in Team can contribute to the Idea of pipeline design. In Hadoop One has to be programming proficient to use its various components like Hive, HDFS, Kafka, etc but in StreamSets all these stages are built-in and ready to use with minor configuration.

Incentivized

• Simplified Improvised Overall data ingestion and Integration Process.
• Support to various Hetrogenous Source systems like RDBMS< Kafka, Salesforce, Key Vault.
• Secure, easy to launch Integration tool.

Incentivized