Description
What does Databricks give you on top of Apache Spark? This lecture walks through the unique capabilities of the Databricks platform and where it runs.
You will see how Databricks brings Spark to the cloud, integrates cloud storage securely, adds ACID transactions through Delta Lake, handles metadata and users with Unity Catalog, manages clusters, speeds up queries with the Photon engine, and offers notebooks, a workspace, administrative controls, an optimised Spark runtime and automation tools (REST APIs, SDKs, CLI and Terraform). It also answers a common question: Databricks is the same on AWS, Azure and GCP, so which one should you choose?
⏱ Chapters
0:00 What this lecture covers
0:20 Databricks: a platform for lakehouse solutions
0:56 Spark in the cloud, independent of Hadoop
1:19 Secure cloud storage integration
1:41 Delta Lake: ACID for your data lake
2:20 Unity Catalog: metadata, users and security
2:53 Cluster management
3:30 The Photon query engine
3:58 Notebooks, workspace and administrative controls
4:43 An optimised Spark runtime
5:14 Automation: REST APIs, SDKs, CLI and Terraform
5:44 Where is Databricks available?
6:10 Which cloud should you choose?
7:11 What actually decides the choice
8:12 Summary
🎓 Full video course (Databricks Data Engineering with AWS): https://www.udemy.com/course/databricks-data-engineering-with-aws/?referralCode=CE4E01DB502854475879
📘 Free tutorials: https://scholarnest.in/
👤 I'm Prashant Kumar Pandey. 25 years of experience designing, developing and delivering data platforms for global enterprises.
🔗 LinkedIn: https://www.linkedin.com/in/prashant-kumar-pandey/
💻 GitHub: https://github.com/learningjournal
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