Databricks Platform

/tldr: The only place serious companies run Spark in 2025

Unity Catalog Delta Live Tables Jobs Lakehouse 2025

2025 LAW

Databricks + Unity Catalog + DLT
= End of data engineering pain

The 2025 Databricks Stack

Bronze

Raw ingest (Kafka, files)

Silver

Clean + conformed + DLT

Gold

Aggregates + BI + ML

Unity Catalog (Your New DB Admin)

What It Gives You

Cross-workspace tables
RBAC + ABAC
Table → Column → Row-level security
Time travel + governance
Delta Sharing

Never Do Again

Hive metastore
dbutils.fs mounts
Hardcoded paths
Manual grants

Delta Live Tables (DLT) = Write SQL/Python → Get Production

import dlt

@dlt.table(comment="Raw JSON → cleaned")
def bronze_events():
    return (spark.readStream.format("kafka")... )

@dlt.table
@dlt.expect_or_drop("valid_id", "id IS NOT NULL")
@dlt.expect_or_fail("valid_ts", "event_ts > '2020'")
def silver_events():
    return (dlt.read_stream("bronze_events")
        .withColumn("date", to_date("event_ts"))
        .dropDuplicates(["id", "event_ts"])
    )

# One click → continuous or triggered pipeline with monitoring, lineage, alerts, retries

DLT = Spark code that never breaks in production

Jobs — The Correct Way

Use Workflows

Multi-task, dependencies, alerts

Task Parameters + Widgets

One job → all envs

Job Clusters or Serverless

No more shared clusters

Secrets → Unity Catalog + Azure Key Vault / AWS Secrets Manager

# Correct way 2025
spark.conf.set("fs.azure.account.key.my.dfs.core.windows.net",
               dbutils.secrets.get("unity-catalog-scope", "storage-key"))

FINAL ANSWER:

Databricks + Unity Catalog + DLT
= The only way to build data platforms in 2025

Everything else is legacy.