Which platform is better for a traditional data warehouse?

Snowflake is better for traditional data warehousing. It's purpose-built for SQL analytics, requires minimal configuration, offers faster query performance for structured data, and has broader enterprise adoption. It excels when your primary need is BI and reporting.

Which platform should I choose for AI and machine learning projects?

Databricks is significantly better for AI/ML. It includes native MLflow integration for model management, supports multiple programming languages, handles unstructured data efficiently, and provides a unified environment for data scientists to build and deploy models without integrations.

How do the pricing models compare?

Both have competitive pricing but different models. Snowflake separates compute and storage with per-second billing, offering more granular cost control. Databricks uses Databricks Units (DBUs), combining compute, storage, and services. For ML workloads, Databricks often costs less; for pure warehousing, Snowflake may be more economical at scale.

Can I use both Snowflake and Databricks together?

Yes, many enterprises use both. Databricks handles data engineering and ML pipeline creation, while Snowflake serves as the central data warehouse for BI and reporting. Delta Sharing and Snowflake's connectors enable seamless data exchange between the platforms.

Which has better data governance and security?

Snowflake has more mature governance features with stronger marketplace controls and broader compliance certifications. However, Databricks has improved significantly with Unity Catalog, providing fine-grained access control across the lakehouse. For highly regulated industries, Snowflake remains the safer choice today.

Snowflake vs Databricks

Updated May 28, 2026

Snowflake

Cloud-native data warehouse platform optimized for analytics and data sharing.

Enterprises needing a pure data warehouse for SQL analytics, BI, and secure cross-organizational data sharing

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Databricks

Lakehouse platform unifying data engineering, analytics, and AI/ML on Apache Spark.

Data science teams, AI-first organizations, and enterprises handling unstructured data with complex ML pipelines

Short Answer

Snowflake is a pure cloud data warehouse optimized for SQL analytics and data sharing, while Databricks is a lakehouse platform combining data engineering and AI/ML with Apache Spark. Snowflake excels at structured data warehousing; Databricks is better for unified data processing and machine learning workloads.

Our Verdict

AI-assisted

Snowflake remains superior for traditional data warehousing, reporting, and secure data sharing across organizations. Databricks leads for unified data analytics, machine learning, and organizations needing multi-language data processing. The choice depends on whether you prioritize data warehousing maturity (Snowflake) or AI/ML-first analytics (Databricks).

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Enterprises needing a pure data warehouse for SQL analytics, BI, and secure cross-organizational data sharing

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Key Differences at a Glance

🔹

Primary Architecture: Databricks wins (Lakehouse (Data Lake + Warehouse) vs Cloud Data Warehouse)

🧠

ML/AI Capabilities: Databricks wins (Native, built-in with MLflow vs Limited, requires integration)

🔹

Data Format Support: Databricks wins (Structured and unstructured data vs Structured data (tables/schemas))

See all 8 differences

Key Facts & Figures

Metric	Snowflake	Databricks	Diff
Starting Monthly Cost(USD)	$2,000-$5,000	$1,500-$4,000	+27%
Setup Time(minutes)	1-3 days	3-7 days	-60%
Query Performance (TPC-DS)(seconds)	15-20

Key Differences

Snowflake

Attribute

Databricks

Cloud Data Warehouse

Primary Architecture

Lakehouse (Data Lake + Warehouse)🏆

Limited, requires integration

ML/AI Capabilities

Native, built-in with MLflow🏆

Structured data (tables/schemas)

Data Format Support

Structured and unstructured data

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Last updated: May 28, 2026AI generated

Primary Architecture

Snowflake

Cloud Data Warehouse

Databricks

Lakehouse (Data Lake + Warehouse)🏆

ML/AI Capabilities

Snowflake

Limited, requires integration

Databricks

Native, built-in with MLflow🏆

Data Format Support

Snowflake

Structured data (tables/schemas)

Databricks

Structured and unstructured data🏆

Query Language

Snowflake

SQL-first approach

Databricks

SQL, Python, Scala, R support🏆

Ease of Setup

Snowflake

Quick, minimal configuration🏆

Databricks

Requires more technical expertise

Data Sharing Features

Snowflake

Snowflake Marketplace, native sharing🏆

Databricks

Delta Sharing (open standard)

Pricing Model

Snowflake

Compute + storage separation

Databricks

DBU (Databricks Units) based

Enterprise Adoption

Snowflake

Wider enterprise adoption🏆

Databricks

Growing, strong in tech/AI

Full Comparison

Attribute	Snowflake	Databricks

Starting Monthly Cost(USD)	$2,000-$5,000	$1,500-$4,000
Base Query Cost(USD per TB scanned)	$2-4 per credit	—
Average Enterprise Contract Value(USD thousands per year)	$200-500	—
Base Cost per TB (Monthly)(USD)	$4-6	—
Monthly Cost (100 GB compressed)(USD)	$1,500	—

Setup Time(minutes)	1-3 days	3-7 days
Setup Time(minutes)	15 minutes	—

Query Performance (TPC-DS)(seconds)	15-20	18-25
Maximum Query Timeout(hours)	Limited by warehouse size	—
Concurrent User Support(scalability level)	Limited by warehouse size, manual tuning	—
Average Query Response Time(seconds)	2-4 seconds	—
Query Latency (1 billion rows)(seconds)	30 seconds	—
Show 2 more attributes Ingestion Throughput(events/sec) 100,000 events/sec — Data Warehouse Query Speed (Typical)(seconds) <5 seconds —

ML/AI Integration Score(out of 10)	4/10	9/10

Global Enterprise Customers(count (2026))	10,000+	6,500+
Market Share 2026(percent)	32%	—

Supported Data Formats(types)	Structured (Parquet, CSV, JSON)	All formats (Delta, Parquet, Images, Videos, Audio)

Data Sharing Standard(technology)	Snowflake Marketplace (proprietary)	Delta Sharing (open standard)
Data Sharing Capability	Native, cross-account/cross-cloud	—
Zero-Copy Cloning	Available (instant, free)	—
Data Retention for Time-Travel(days)	90 days	—

Multi-Language Support(languages)	SQL primarily	SQL, Python, Scala, R, Java

Supported Cloud Providers(number of platforms)	3 (AWS, Azure, GCP)	—
Available Cloud Providers(count)	AWS, Azure, GCP	—

Setup Time to First Query(minutes)	20-30 minutes	—

Data Marketplace Size(number of datasets)	1,000+ datasets	—

Annual Customer Growth Rate (2025)(percent)	22% YoY	—

Compute-Storage Decoupling	Complete separation	—

Time to Production (median)(weeks)	1-3 weeks	—

Compression Ratio(ratio)	4:1 to 8:1	—

Licensing Model	Consumption-based (compute + storage)	—

Learning Curve (1-10 scale)(difficulty rating)	3/10 (very easy)	—

Snowflake

Databricks

Starting Monthly Cost(USD)

$2,000-$5,000

$1,500-$4,000

Base Query Cost(USD per TB scanned)

$2-4 per credit

—

Average Enterprise Contract Value(USD thousands per year)

$200-500

—

Base Cost per TB (Monthly)(USD)

$4-6

—

Monthly Cost (100 GB compressed)(USD)

$1,500

—

Setup Time(minutes)

1-3 days

3-7 days

Setup Time(minutes)

15 minutes

—

Query Performance (TPC-DS)(seconds)

15-20

18-25

Maximum Query Timeout(hours)

Limited by warehouse size

—

Concurrent User Support(scalability level)

Limited by warehouse size, manual tuning

—

Average Query Response Time(seconds)

2-4 seconds

—

Query Latency (1 billion rows)(seconds)

30 seconds

—

Show 2 more attributes

Ingestion Throughput(events/sec)

100,000 events/sec

—

Data Warehouse Query Speed (Typical)(seconds)

<5 seconds

—

ML/AI Integration Score(out of 10)

4/10

9/10

Global Enterprise Customers(count (2026))

10,000+

6,500+

Market Share 2026(percent)

32%

—

Supported Data Formats(types)

Structured (Parquet, CSV, JSON)

All formats (Delta, Parquet, Images, Videos, Audio)

Data Sharing Standard(technology)

Snowflake Marketplace (proprietary)

Delta Sharing (open standard)

Data Sharing Capability

Native, cross-account/cross-cloud

—

Zero-Copy Cloning

Available (instant, free)

—

Data Retention for Time-Travel(days)

90 days

—

Multi-Language Support(languages)

SQL primarily

SQL, Python, Scala, R, Java

Supported Cloud Providers(number of platforms)

3 (AWS, Azure, GCP)

—

Available Cloud Providers(count)

AWS, Azure, GCP

—

Setup Time to First Query(minutes)

20-30 minutes

—

Data Marketplace Size(number of datasets)

1,000+ datasets

—

Annual Customer Growth Rate (2025)(percent)

22% YoY

—

Compute-Storage Decoupling

Complete separation

—

Time to Production (median)(weeks)

1-3 weeks

—

Compression Ratio(ratio)

4:1 to 8:1

—

Licensing Model

Consumption-based (compute + storage)

—

Learning Curve (1-10 scale)(difficulty rating)

3/10 (very easy)

—

Full Comparison

Attribute	Snowflake	Databricks

Starting Monthly Cost(USD)	$2,000-$5,000	$1,500-$4,000
Base Query Cost(USD per TB scanned)	$2-4 per credit	—
Average Enterprise Contract Value(USD thousands per year)	$200-500	—
Base Cost per TB (Monthly)(USD)	$4-6	—
Monthly Cost (100 GB compressed)(USD)	$1,500	—

Setup Time(minutes)	1-3 days	3-7 days
Setup Time(minutes)	15 minutes	—

Query Performance (TPC-DS)(seconds)	15-20	18-25
Maximum Query Timeout(hours)	Limited by warehouse size	—
Concurrent User Support(scalability level)	Limited by warehouse size, manual tuning	—
Average Query Response Time(seconds)	2-4 seconds	—
Query Latency (1 billion rows)(seconds)	30 seconds	—
Show 2 more attributes Ingestion Throughput(events/sec) 100,000 events/sec — Data Warehouse Query Speed (Typical)(seconds) <5 seconds —

ML/AI Integration Score(out of 10)	4/10	9/10

Global Enterprise Customers(count (2026))	10,000+	6,500+
Market Share 2026(percent)	32%	—

Supported Data Formats(types)	Structured (Parquet, CSV, JSON)	All formats (Delta, Parquet, Images, Videos, Audio)

Data Sharing Standard(technology)	Snowflake Marketplace (proprietary)	Delta Sharing (open standard)
Data Sharing Capability	Native, cross-account/cross-cloud	—
Zero-Copy Cloning	Available (instant, free)	—
Data Retention for Time-Travel(days)	90 days	—

Multi-Language Support(languages)	SQL primarily	SQL, Python, Scala, R, Java

Supported Cloud Providers(number of platforms)	3 (AWS, Azure, GCP)	—
Available Cloud Providers(count)	AWS, Azure, GCP	—

Setup Time to First Query(minutes)	20-30 minutes	—

Data Marketplace Size(number of datasets)	1,000+ datasets	—

Annual Customer Growth Rate (2025)(percent)	22% YoY	—

Compute-Storage Decoupling	Complete separation	—

Time to Production (median)(weeks)	1-3 weeks	—

Compression Ratio(ratio)	4:1 to 8:1	—

Licensing Model	Consumption-based (compute + storage)	—

Learning Curve (1-10 scale)(difficulty rating)	3/10 (very easy)	—

Snowflake

Databricks

Starting Monthly Cost(USD)

$2,000-$5,000

$1,500-$4,000

Base Query Cost(USD per TB scanned)

$2-4 per credit

—

Average Enterprise Contract Value(USD thousands per year)

$200-500

—

Base Cost per TB (Monthly)(USD)

$4-6

—

Monthly Cost (100 GB compressed)(USD)

$1,500

—

Setup Time(minutes)

1-3 days

3-7 days

Setup Time(minutes)

15 minutes

—

Query Performance (TPC-DS)(seconds)

15-20

18-25

Maximum Query Timeout(hours)

Limited by warehouse size

—

Concurrent User Support(scalability level)

Limited by warehouse size, manual tuning

—

Average Query Response Time(seconds)

2-4 seconds

—

Query Latency (1 billion rows)(seconds)

30 seconds

—

Show 2 more attributes

Ingestion Throughput(events/sec)

100,000 events/sec

—

Data Warehouse Query Speed (Typical)(seconds)

<5 seconds

—

ML/AI Integration Score(out of 10)

4/10

9/10

Global Enterprise Customers(count (2026))

10,000+

6,500+

Market Share 2026(percent)

32%

—

Supported Data Formats(types)

Structured (Parquet, CSV, JSON)

All formats (Delta, Parquet, Images, Videos, Audio)

Data Sharing Standard(technology)

Snowflake Marketplace (proprietary)

Delta Sharing (open standard)

Data Sharing Capability

Native, cross-account/cross-cloud

—

Zero-Copy Cloning

Available (instant, free)

—

Data Retention for Time-Travel(days)

90 days

—

Multi-Language Support(languages)

SQL primarily

SQL, Python, Scala, R, Java

Supported Cloud Providers(number of platforms)

3 (AWS, Azure, GCP)

—

Available Cloud Providers(count)

AWS, Azure, GCP

—

Setup Time to First Query(minutes)

20-30 minutes

—

Data Marketplace Size(number of datasets)

1,000+ datasets

—

Annual Customer Growth Rate (2025)(percent)

22% YoY

—

Compute-Storage Decoupling

Complete separation

—

Time to Production (median)(weeks)

1-3 weeks

—

Compression Ratio(ratio)

4:1 to 8:1

—

Licensing Model

Consumption-based (compute + storage)

—

Learning Curve (1-10 scale)(difficulty rating)

3/10 (very easy)

—

Snowflake vs Databricks

Snowflake

Databricks

Short Answer

Our Verdict

Track this comparison

Key Differences at a Glance

Key Facts & Figures

Key Differences

Related Comparisons

Related Articles

Explore Entities

More Products

People Also Compare

Full Comparison

Visual Comparison

Pros & Cons

Snowflake

Pros

Cons

Databricks

Pros

Cons

Frequently Asked Questions

Resources & Learn More

Where to Buy

Wikipedia

Videos

Full Comparison

Visual Comparison

Snowflake vs Databricks

Snowflake

Databricks

Short Answer

Our Verdict

🔔Track this comparison

Key Differences at a Glance

Key Facts & Figures

Key Differences

Related Comparisons

Related Articles

Explore Entities

More Products

People Also Compare

Full Comparison

Visual Comparison

Pros & Cons

Snowflake

Pros

Cons

Databricks

Pros

Cons

Frequently Asked Questions

Resources & Learn More

Where to Buy

Wikipedia

Videos

Full Comparison

Visual Comparison

Track this comparison