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16 articles found

The Lakehouse Lie: Why Choosing Between AWS and Databricks Isn’t About Technology

Evaluating the long-term implications of choosing cloud-native storage solutions versus managed lakehouse platforms for enterprise data teams.

#aws#databricks#unity-catalog

databricks

The Death of PySpark? Why SQL Rules the Gold Layer

Data pipelines are quietly abandoning Spark processing for final aggregation layers. The shift isn’t about performance, it’s about who actually maintains the code.

#databricks#pyspark

airflow

Airflow and Hadoop Are Dead (And Other Lies Your Cloud Vendor Told You)

The provocative claim that ‘no one uses Airflow or Hadoop in 2026’ sparked a firestorm in data engineering circles. We dissect the reality behind the hyperbole, the true cost of legacy orchestration, and why your DAGs might be on life support.

#airflow#Cloud Native#Data Engineering...

cloud infrastructure

Europe’s Data Platform Dilemma: Why Homegrown Databricks Alternatives Keep Missing the Mark

With U.S. legal frameworks threatening European data sovereignty, companies are scrambling for alternatives. But the search reveals a harsh reality: viable European-born data platforms barely exist, and AWS’s €7.8B compromise might be the best bad option.

#cloud infrastructure#data sovereignty#databricks...

aws

The Databricks Tax: Why Small Teams Can’t Afford to Build Their Own Lakehouse

Small data teams face a brutal choice: pay Databricks’ premium or sink months into stitching together AWS services that will haunt them at 3 AM. The real cost isn’t infrastructure, it’s velocity.

#aws#databricks

databricks

Databricks Serverless Jobs Benchmark: The Shocking Cost of Convenience

New performance benchmarks compare Databricks Classic vs. Serverless Jobs and DBSQL across cost, latency, and throughput, offering actionable insights for engineering teams evaluating migration.

#databricks#serverless

dag-complexity

Data Modeling Is Killing Your PySpark Performance, Not Join Optimization

A technical post-mortem on why a 50k-row table brought down a Databricks cluster, exposing the dangerous gap between software engineering instincts and distributed data architecture

#dag-complexity#data-modeling#databricks...

data-architecture

Medallion Architecture: 30-Year-Old Patterns in a Databricks Coat of Paint

A growing backlash questions whether Databricks’ popular medallion architecture represents genuine innovation or simply repackages decades-old data modeling patterns with fresh marketing.

#data-architecture#data-warehouse#databricks...

cloud migration

From On-Prem Cloudera to Cloud Databricks: The Migration Challenge

A data engineer’s real-world journey from legacy Hadoop stacks to cloud-native Databricks reveals the uncomfortable truths about enterprise migration: hidden costs, steep learning curves, and the architectural shifts that can make or break your modernization efforts.

#cloud migration#cloudera#Data Engineering...

bill-inmon

The Data Warehouse Blues: Bill Inmon Says We Lost the Vowels

Data warehousing pioneer Bill Inmon argues modern platforms like Databricks and Snowflake have confused storage with integration, reducing data warehouses to rubble. Practitioners push back: is it the technology, or have we just stopped doing the hard work?

#bill-inmon#data-integration#data-warehousing...

career-growth

The Data Engineer’s Dilemma: Snowflake’s AI Gold Rush vs Databricks’ Open Future

An in-depth analysis of whether data engineers should double down on Snowflake’s AI-driven evolution or pivot to Databricks for long-term career growth, based on platform trajectories and market demand.

#career-growth#databricks#snowflake

cost-optimization

The Databricks Exit: Why Broke Teams Are Building Better Data Stacks on Kubernetes

Budget cuts are forcing teams off Azure Databricks and onto open-source alternatives. The twist? They’re discovering more flexible, composable architectures that might be superior, even if they could afford the managed platforms.

#cost-optimization#data-engineering#databricks...

data-architecture

The Medallion Architecture Debate: Why Nobody Agrees on Silver vs. Gold

Exploring the hidden inconsistencies in how teams implement raw-silver-gold layering models, from transformation logic disagreements to the platinum layer controversy.

#data-architecture#data-engineering#databricks...

data-engineering

The Fivetran-dbt “Marriage of Convenience” That’s Quietly Declaring War on Snowflake

The merger between Fivetran and dbt Labs isn’t just consolidation, it’s a strategic power play to flip the data stack hierarchy and make warehouses the commodities, not the kings.

#data-engineering#databricks#dbt...

data-catalog

The Great Metadata Unification War: Are We Trading Chaos for Vendor Prison?

As Databricks’ Unity Catalog goes all-in, companies face a stark choice: embrace vendor lock-in or build fragile federated systems.

#data-catalog#data-governance#databricks...

apache-iceberg

The Death of Data Partitioning? Clustering Takes Over in Modern Data Lakes

Emerging shift from traditional data partitioning to clustering techniques in Delta Lake, Iceberg, Snowflake, and Databricks, and what it means for data engineering best practices.

#apache-iceberg#data-engineering#data-lakes...