Cloud Data Warehouse Guide: How to Choose in 2025

Choosing a cloud data warehouse in 2025 isn't just about picking between Redshift, BigQuery, or Snowflake anymore. It’s a high-stakes decision with a new lineup of challengers shaking up the modern data stack. This guide helps you cut through the noise and make an informed decision.

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Who’s in the Ring?

The core platforms still dominate:

• Snowflake – The enterprise darling with cross-cloud flexibility

• BigQuery – Serverless simplicity at massive scale

• Redshift (RA3) – Optimized for deep AWS integration

But serious challengers have emerged:

• Databricks SQL – Unified Lakehouse + ML/AI powerhouse

• Firebolt – Lightning-fast SQL with a performance-first mindset

• ClickHouse – Open-source OLAP for dev-led teams

• DuckDB/MotherDuck – Lightweight hybrid analytics

The 2024 Forrester Wave™ on Data Lakehouses highlights this shift: Snowflake, Databricks, and BigQuery are seen as leaders, with Databricks leading in AI-powered automation, ML integration, and workload flexibility. Snowflake and Google’s BigQuery are praised for ease of use, multicloud scale, and automation.

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Match Your Stack to Your Workloads

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Platform Rundown

🔷 Snowflake

• Cross-cloud support, strong ecosystem

• Auto-scaling compute, data sharing, governance

• Ideal for BI, data collaboration, and governed pipelines

🔶 BigQuery

• Fully serverless, per-query or flat-rate

• Great for ad-hoc analysis, ML integration, and GCP workloads

• Excellent for teams that want low ops

🔴 Redshift (RA3)

• AWS-native performance with Spectrum and AQUA cache

• Ideal for teams already inside the AWS ecosystem

• Best for cost-conscious steady workloads

🟣 Databricks SQL

• Unified Lakehouse platform with Delta Lake

• AI/ML-ready with Photon engine and native notebooks

• Strongest roadmap in genAI, LLM integration, and workload automation【59†source】

🟠 Firebolt

• Sub-second queries, efficient indexing

• Built for product and user behavior analytics

• Lightweight with strong performance gains

🟡 ClickHouse

• Open-source OLAP engine with ClickHouse Cloud

• Best for engineering-led teams prioritizing speed and control

🟤 DuckDB / MotherDuck

• Lightweight SQL OLAP engine with cloud sync

• Great for prototyping, embedded analytics, or local-first workflows

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Final Take

There’s no universal winner. Your best cloud data warehouse depends on your:

• Cloud strategy (AWS/GCP/Azure/multi-cloud)

• Workload type (steady, bursty, app-driven)

• Team skills (analysts vs engineers)

• Desire for managed simplicity vs deep customization

In 2025, the leaders still lead—but the challengers are gaining ground. Choose based on fit, not just familiarity.