Azure Databricks
Design AI with Apache Spark™-based analytics.
Overview
Azure Databricks is a data analytics platform optimized for the Microsoft Azure cloud services platform. Azure Databricks offers three environments for developing data intensive applications: Databricks SQL, Databricks Data Science & Engineering, and Databricks Machine Learning.
Key Resources
| Homepage: | https://learn.microsoft.com/azure/databricks/ |
|---|---|
| Pricing: | https://azure.microsoft.com/pricing/details/databricks/ |
| SLA: | https://azure.microsoft.com/support/legal/sla/databricks/ |
| Newsfeed: | RSS |
News
| Date | News |
|---|---|
| 4/22/2024 |
Azure Databricks materialized views and streaming tables Billing change
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| 4/11/2024 |
Why Do we Need RAG?
RAG stands for Retrieval-Augmented Generation, which is a technique for improving the accuracy and reliability of generative AI models with facts retrieved from external...
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| 12/11/2023 |
Many organisations store their data in a centralised data lake on Azure Storage accounts. In this post we will look at a solution to scale the secure network access between the centralised data...
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| 11/15/2023 |
Users can now select AMD-based confidential VMs for their Azure Databricks cluster driver node and cluster worker nodes.
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| 8/1/2023 |
Enhanced Security and Compliance (ESC) add-on helps simplify the complexity of meeting security and regulatory requirements for Azure Databricks customers.
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| 6/5/2023 |
Sagar Lad is a Technical Solution Architect with a leading multinational software company and has deep expertise in implementing Data & Analytics solutions for large enterprises using Cloud and...
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| 5/23/2023 |
Users can now select AMD-based confidential VMs for their Azure Databricks cluster driver node and cluster worker nodes.
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| 5/3/2023 |
Serverless SQL for Azure Databricks is now generally available.
This capability provides instant compute to users for their BI and SQL workloads, with minimal management required.
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