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Need clarity on Synapse and Data Factory and Databricks

BathiniShirish-2885 60 Reputation points
2025-06-30T05:23:14.67+00:00

Please spare few mins on my question clearly .

I am struggling to convince the customer/interviewer when they need clarification on what service to be used for ingestion , transformation , orchestration , data modelling .

I answer this way " We leverage ADF to Data ingestion , transformation and orchestration. Databricks for , In case large datasets, streaming , AI/ML . Synapse is used for DW, bigdata analytics, Prepare for Datamodel "

Is it OK and cost effective for customer to use Databricks, ADF, Synapse in a single development project ?

Interviewer saying , don't we go with synapse when we have everything in one plotform ?

Please help in understanding all these services ( Actually I know about all services , but unable to convince customer )

Thank You

Azure Synapse Analytics
Azure Synapse Analytics

An Azure analytics service that brings together data integration, enterprise data warehousing, and big data analytics. Previously known as Azure SQL Data Warehouse.

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  1. Venkat Reddy Navari 5,840 Reputation points Microsoft External Staff Moderator
    2025-06-30T07:20:21.7+00:00

    Hi @BathiniShirish-2885 Here’s a quick breakdown to help explain when and why you'd use ADF, Synapse, or Databricks whether on their own or together and how to handle the common question: Can’t we just use Synapse for everything

    What each tool does best:

    Azure Data Factory (ADF): Best for ingestion and orchestration. It moves data across systems and manages pipeline scheduling.

    Databricks: Ideal for heavy transformations, streaming, and machine learning, especially with large datasets.

    Synapse Analytics: Suited for data modeling, warehousing, and analytics, with seamless Power BI integration.

    • How they usually work together: Use ADF to ingest and orchestrate → Databricks to clean and process → Synapse to model and analyze.

    Why not just use Synapse for everything?

    While Synapse can do a bit of everything (pipelines, Spark, SQL), it’s not always the best tool for every task:

    • Databricks handles big data and ML more efficiently.
    • ADF pipelines are more mature and flexible than Synapse's built-in ones.
    • Trying to do everything in Synapse can lead to performance issues or cost inefficiencies in complex projects.

    Cost-effectiveness:

    Yes, using all three can be cost-effective. Each service is optimized for specific workloads and operates on a pay-per-use basis, which helps manage cost better than overloading one platform.

    How to explain it simply:

    We use each tool where it fits best ADF for orchestration, Databricks for complex processing, and Synapse for analytics. That way we balance performance, cost, and flexibility.

    Hope this helps. If this answers your query, do click Accept Answer and Yes for was this answer helpful. And, if you have any further query do let us know.

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  1. Nandan Hegde 36,801 Reputation points MVP Volunteer Moderator
    2025-06-30T07:07:30.7366667+00:00

    Azure synapse has close integration with MSFT ecosystem like Power BI, Dataverse, Azure purview etc.

    And Data pipelines within synapse are equivalent to ADF and notebooks to some extents are equivalent for Databricks notebooks.

    Databricks is for advanced big data, data science, machine learning, and streaming workloads over Synapse.

    So for normal data analytics and reportings, Synapse can be an easier use case

    1 person found this answer helpful.
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