Databricks Vs Snowflake off Page PDF submission.pdf

This presentation compares the features and use cases of Databricks and Snowflake, two prominent platforms in the realm of data analytics and management.

1. Understanding the Differences Between
Databricks and Snowflake

2. Introduction:
This presentation compares the features and use cases of
Databricks and Snowflake, two prominent platforms in the
realm of data analytics and management.

3. Databricks Overview
●Features: Databricks offers integrated workspace for
collaboration, Apache Spark-based analytics, and automated
cluster management.

●Use Cases: Ideal for data engineering, machine learning
model training, and real-time analytics.

4. Snowflake Overview
●Features: Snowflake provides a cloud-native data
warehouse platform with separate compute and storage
layers, supporting ANSI SQL queries.

●Use Cases: Suitable for data warehousing, data sharing
across organizations, and scalable analytics.

5. ●Databricks excels in processing large-scale data sets and
real-time analytics due to its in-memory processing
capabilities.

●Snowflake offers scalable performance with separate
compute and storage layers, optimizing query performance
and concurrency.

Performance Comparison

6. Architecture Comparison
●Databricks architecture revolves around Apache Spark,
enabling distributed data processing and machine
learning capabilities.

●Snowflake’s architecture separates storage and compute,
allowing independent scaling and efficient resource
utilization.

7. Use Case Comparison
●Use Databricks for real-time analytics, ETL (Extract,
Transform, Load) processes, and machine learning model
training.

●Use Snowflake for data warehousing, ad-hoc querying,
data sharing across organizations, and scalable analytics.

8. Pricing and Cost Considerations
●Databricks pricing typically involves compute resources
and storage usage, with different tiers based on usage
and features.

●Snowflake offers usage-based pricing models, including
on-demand and prepaid options, with costs varying by
storage and compute resources used.

9. Conclusion
●Both platforms excel in different aspects of data
management and analytics.

●Choosing between Databricks and Snowflake depends
on specific organizational needs, data workload
characteristics, and budget considerations.
Read the detailed blog, here , and understand which data
platform works best for your enterprise.

10. Thank you!