Fivetran vs. StreamSets DataOps Platform

Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.

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

• Easily connects to source data using delivered connectors
• Transforms data into standard models and schemas
• Has very good documentation to help quickly setup connectors

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

• More detailed logging
• More flexible choices for time range over which records are synced
• More options for masking and excluding sensitive data

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

Just need to input connection info.

Incentivized

It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

Incentivized

We never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.

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

• Business and product data now co-located in the warehouse
• Dashboards can be built using data from all corners of the business
• Better visibility into customer health, product usage, business financials, and more
• Enabled high-traffic operational dashboards that increase efficiency of our sales and ops teams

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