Snowflake Applications & Collaboration

Name: Snowflake Applications & Collaboration
Brand: Snowflake
Rating: 4.6 (1674 reviews)

Leader

Where data does more

Est 2012|Valuation $118.2B|Raised $5.8B

LinkedIn 1.4M|Website|Web traffic 4.1M|FTEs 9,060|HQ Menlo Park, CA

MarketsData Warehouses & Lakehouses

Snowflake Applications & Collaboration screenshot

01Competitive Landscape

Narrative analysis

Snowflake vs Databricks for collaboration - Snowflake: Secure Data Sharing is designed as a governed sharing model within Snowflake accounts, with listing and app distribution mechanisms intended to simplify packaging and installation. - Databricks: Emphasizes notebook-first compute (including Python) and open-protocol sharing (Delta Sharing) with different tradeoffs for compute paradigms and extensibility. - Cost modeling: Both vendors present cross-region and cross-cloud considerations; buyers should model network, replication, and compute costs for intended collaboration patterns. Marketplace and app distribution - Snowflake Native Apps: Apps are installed and run inside the customer's Snowflake account, which affects procurement, privileges, and operational responsibilities. - Databricks Apps: Focuses on internal app deployment within Databricks, supporting multiple frameworks and different provisioning models. Adoption signals - Mindshare metrics from review platforms are directional signals rather than formal market share measures. Vendor comparative pages should be treated as vendor-provided perspectives rather than independent benchmarks.

	Snowflake Applications & Collaboration	Databricks (Sharing / Clean Rooms / Marketplace / Apps)	AWS-native approach (Redshift + AWS Clean Rooms + ecosystem)
Starting Price	Published consumption-based pricing model; consult vendor for specifics	Published consumption-based pricing model; consult vendor for specifics	Published consumption-based pricing across multiple services; consult vendor for specifics
Primary use case	Organizations seeking governed in-place sharing and Snowflake-native app distribution	Organizations favoring open sharing, notebook-first data science, and Spark/Python workflows	Organizations standardized on AWS and willing to integrate multiple services for sharing and collaboration
Key strength	In-account sharing and Marketplace distribution model; Native App packaging and install into customer accounts	Delta Sharing interoperability and a Python/Spark-oriented compute model; broader notebook and ML ecosystem	Deep integration with AWS services, IAM, and a broad portfolio of managed services
Key weakness	Cost predictability and Native App operational constraints; potential dependency on Snowflake account model	Cross-region/cloud egress and governance maturity depend on Unity Catalog/Delta Sharing adoption	Requires more assembly of services for a cohesive app distribution story; more DIY integration

01Competitive Landscape

Narrative analysis

Snowflake vs Databricks for collaboration

Snowflake: Secure Data Sharing is designed as a governed sharing model within Snowflake accounts, with listing and app distribution mechanisms intended to simplify packaging and installation.
Databricks: Emphasizes notebook-first compute (including Python) and open-protocol sharing (Delta Sharing) with different tradeoffs for compute paradigms and extensibility.
Cost modeling: Both vendors present cross-region and cross-cloud considerations; buyers should model network, replication, and compute costs for intended collaboration patterns.

Marketplace and app distribution

Snowflake Native Apps: Apps are installed and run inside the customer's Snowflake account, which affects procurement, privileges, and operational responsibilities.
Databricks Apps: Focuses on internal app deployment within Databricks, supporting multiple frameworks and different provisioning models.

Adoption signals

Mindshare metrics from review platforms are directional signals rather than formal market share measures. Vendor comparative pages should be treated as vendor-provided perspectives rather than independent benchmarks.

	Snowflake Applications & Collaboration	Databricks (Sharing / Clean Rooms / Marketplace / Apps)	AWS-native approach (Redshift + AWS Clean Rooms + ecosystem)
Starting Price	Published consumption-based pricing model; consult vendor for specifics	Published consumption-based pricing model; consult vendor for specifics	Published consumption-based pricing across multiple services; consult vendor for specifics
Primary use case	Organizations seeking governed in-place sharing and Snowflake-native app distribution	Organizations favoring open sharing, notebook-first data science, and Spark/Python workflows	Organizations standardized on AWS and willing to integrate multiple services for sharing and collaboration
Key strength	In-account sharing and Marketplace distribution model; Native App packaging and install into customer accounts	Delta Sharing interoperability and a Python/Spark-oriented compute model; broader notebook and ML ecosystem	Deep integration with AWS services, IAM, and a broad portfolio of managed services
Key weakness	Cost predictability and Native App operational constraints; potential dependency on Snowflake account model	Cross-region/cloud egress and governance maturity depend on Unity Catalog/Delta Sharing adoption	Requires more assembly of services for a cohesive app distribution story; more DIY integration