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Forum Posts

szymon_dybczak
by Esteemed Contributor III
  • 894 Views
  • 3 replies
  • 2 kudos

Unity Catalog-only workspace for new Azure Databricks deployments

Big shift coming for Azure Databricks usersStarting 30 September 2026, all new Azure Databricks workspaces will be Unity Catalog only.- No DBFS root.- No Hive Metastore.- No legacy runtimes below 13.3 LTS.- No “old way” of doing things.Disabling DBFS...

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  • 894 Views
  • 3 replies
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szymon_dybczak
Esteemed Contributor III
  • 2 kudos

Hi guys,There was an email message sent by Azure Databricks with this information. So no direct link, just information sent by Databricks to users.

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antoalphi
by New Contributor III
  • 258 Views
  • 1 replies
  • 1 kudos

Databricks Lakeflow Connect for MySQL

In Databricks Lakeflow Connect for MySQL (currently in public preview), Databricks recommends limiting each ingestion pipeline to around 250 tables, with validated testing up to 1 TB of snapshot data.However, in real-world enterprise scenarios, custo...

  • 258 Views
  • 1 replies
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Sumit_7
Honored Contributor III
  • 1 kudos

@antoalphi I think you have already answered in the first line itself - Public Preview -- meaning not full developed for general/real use. Hence it comes with limitations or bugs which will be covered in General Available. Though still you may consid...

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Brahmareddy
by Esteemed Contributor
  • 293 Views
  • 1 replies
  • 2 kudos

Austin’s Practical Data + AI Meetup

Austin data community, this one looks worth attending. Databricks DevConnect Austin is happening on Tuesday, April 14, 2026, from 5:00 PM to 9:00 PM at Qubika Office in Austin. It is a technical meetup built for data and AI practitioners who want rea...

  • 293 Views
  • 1 replies
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Sumit_7
Honored Contributor III
  • 2 kudos

Great opportunity to connect with amazing and like minded minds.Would love to see more such events in India as well, specially in Lucknow, Noida, Bhopal -- Events Team

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antoalphi
by New Contributor III
  • 148 Views
  • 0 replies
  • 1 kudos

Solution Proposal (Cost-Optimized Architecture)

Core IdeaDon’t let “1 pipeline = 1 always-on cluster” become your cost trap.Instead, design for controlled parallelism + shared compute + smart grouping. A. Pipeline Sharding Strategy (Not Blind Splitting)Instead of randomly splitting 6,700 tables i...

  • 148 Views
  • 0 replies
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VinayKumarB
by Databricks Partner
  • 614 Views
  • 1 replies
  • 6 kudos

MCP Servers on Databricks

MCP Servers on DatabricksGenerative AI is evolving rapidly, and one of the most exciting developments is standardizing how models interact with external systems. Let me walk you through how we got here and why the Model Context Protocol (MCP)—especia...

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  • 614 Views
  • 1 replies
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Sumit_7
Honored Contributor III
  • 6 kudos

Insightful, detailed and incisive guide @VinayKumarB. Keep posting!

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szymon_dybczak
by Esteemed Contributor III
  • 253 Views
  • 2 replies
  • 3 kudos

Notifications for scheduled refreshes - now in Beta

If you’ve ever worked with scheduled refreshes for Materialized Views or Streaming Tables, you probably know this pain. If your DDL-scheduled MV or ST refresh failed, nothing happened. No email, no alert, no indication that your data was stale (until...

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Advika
Community Manager
  • 3 kudos

Welcome back, @szymon_dybczak! That silent failure pain was real. These alerts are a massive win for everyone’s sanity. Thanks for the heads-up!

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shubham_meshram
by Databricks Partner
  • 2594 Views
  • 1 replies
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When Did the Data Go Wrong? Using Delta Lake Time Travel for Investigation in Databricks

I. IntroductionData pipelines are the lifeblood of modern data-driven organizations. However, even the most robust pipelines can experience unexpected issues: data corruption, erroneous updates, or sudden data drops. When these problems occur, quickl...

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  • 2594 Views
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deepakachary9
New Contributor II
  • 1 kudos

Great thought to use delta time travel to determine when data drift starts!But this only works as long as retention policies allow it. With vacuum and stricter runtime enforcement in newer dbx versions, older snapshots may not be there when you need ...

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Louis_Frolio
by Databricks Employee
  • 526 Views
  • 7 replies
  • 6 kudos

What's Your Biggest AI Pet Peeve?

Hey Team, in my last post I asked how much AI has actually changed your day to day, and the responses were fantastic. But let's talk about the other side for a minute. I'll go first — I've started second-guessing almost everything I see on social med...

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  • 526 Views
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balajij8
Contributor III
  • 6 kudos

AI tools generate code & pipelines that work functionally but ignore efficiency, scalability & cloud implications. I have bumped into belowCode generated by AI does a SQL cross join as its simple for most natural language queries that works but kills...

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Ashwin_DSA
by Databricks Employee
  • 1697 Views
  • 3 replies
  • 9 kudos

Databricks Multi-Table Transactions - Part 1

If you've ever worked on an insurance data warehouse, or really any warehouse where data arrives from different systems at different times, you know the pain of keeping things in sync. I spent years building data warehouses for a property and casual...

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  • 1697 Views
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Ashwin_DSA
Databricks Employee
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Link to Part 2   

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