Explore a comprehensive conference talk that delves into the decision-making process for selecting the right Azure data engineering tool. Compare Azure Data Factory, Azure Databricks, and Azure Synapse Analytics, understanding their strengths, limitations, and ideal use cases. Learn about each tool's capabilities, including Azure Data Factory's canvas, Databricks' notebook environment, and Synapse Analytics' comprehensive platform. Discover implementation costs, performance comparisons, and benchmarks to guide your choice. Follow Alice's journey as she navigates through these options, and gain insights into when to use each tool. Utilize a decision-making chart to help determine the best fit for your specific data engineering project needs.
Azure Data Engineering Tools: Choosing Between Data Factory, Databricks, and Synapse Analytics
Overview
Syllabus
Intro
Agenda
Household announcements
Who is Alice
What does Alice need
What does the data look like
What do we know
What do you think
What is Azure Data Factory
Azure Data Factory Canvas
Why you should not use Azure Data Factory
What is Databricks
Who can use Databricks
Why use Databricks
Notebooks
Technical Knowledge
Synapse Analytics
Multiple disciplines
Comprehensive platform
Languages
Notebook
Error in Databricks
Error in Synapse Analytics
Lets Compare
What did Alice learn
What should Alice choose
Comparing tools
Comparing Spark clusters
Optimized Spark
Implementation Costs
Performance
Performance comparison
Cost comparison
Conclusion
Benchmarks
Summary
Maturity vs integration
Which should you choose
Its not that easy
When to use Azure Data Factory
When to use Databricks
When to use Synapse
Chart to make a decision
Taught by
SQLBits
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Implement a data lakehouse analytics solution with Azure Databricks
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Transfer and transform data with Azure Synapse Analytics pipelines
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Model, query, and explore data in Azure Synapse
