Data is the lifeblood of modern enterprises. As data volumes grow, sharing information both within the organization and externally becomes essential to unblock its full potential. Traditionally, organizations have relied on methods like FTP, email, shared drives, and APIs for data sharing. However, these methods often involve substantial effort from both the provider and the consumer, resulting in challenges like synchronization issues, data redundancy, and inconsistent updates.
Snowflake, a modern cloud data platform, tackles these challenges through its innovative “Share” feature.
What is Snowflake Share?
Snowflake Share is a breakthrough feature enabling frictionless and consistent data sharing without traditional complexities. Below are some of its key attributes:
- Provider and Consumer Model
The entity sharing the data is the Provider, while the entity consuming it is the Consumer. Providers can grant consumers access to their data without the need for duplication. Key points include:
- Consumers with Snowflake accounts can access shared data seamlessly as though it resides in their own account.
- If not, the provider can create a reader account, giving the consumer access via dedicated credentials.
- Zero Copy Architecture
Snowflake’s sharing mechanism eliminates the need to create duplicate copies of data. Updates to the source data are immediately reflected for consumers, eliminating inconsistencies.
- Monetization via Marketplace
Providers can list their data on Snowflake’s Data Marketplace, allowing for monetization, enabling broader access.
- No ETL Effort
Neither the provider nor the consumer needs to build Extract-Transform-Load (ETL) processes, saving significant development effort.
Methods of Sharing Data in Snowflake
Snowflake offers multiple ways to share data, catering to various use cases:
1. Direct Data Sharing
This is a one-to-one or one-to-many sharing model for consumers in the same cloud region.
Use Cases:
- Sharing data with partners, vendors, customers, or internal teams.
- Non-Snowflake users can access data using a reader account.
- Cost Model: Compute costs are billed to the consumer (if they have a Snowflake account) or to the provider (for reader accounts).
2. Listings: Curated Data Sharing
Listings allow providers to share specific datasets enriched with metadata, making them easier to discover and understand.
Key Features:
- Define and share specific datasets (tables, views, or materialized views).
- Add metadata, usage guidelines, and sample queries to enhance understanding.
- Control access and manage versions for consumers.
- Monetize datasets by publishing them on the Snowflake Marketplace.
Use Case: Ideal for organizations seeking to package data as a product.
3. Snowflake Data Marketplace
A public data exchange where organizations offer datasets for free or paid access. Data remains within the provider’s account, ensuring no duplication.
Use Cases:
- Monetize data assets by offering valuable insights to data consumers.
- Cater to unknown consumers, such as research organizations or businesses seeking weather or healthcare data.
- Facilitate cross-region or cross-cloud data sharing instantly.
4. Data Exchanges: Multi-Party Collaboration
A centralized hub for sharing data with multiple consumers, enabling collaboration across accounts. This is particularly useful to collaborate with selected groups of internal or external users like suppliers, vendors etc. Using Data exchange organizations can manage access, security and track usage as well. Data exchange admin manages members, members can publish listing and grant access. Consumers can browse listings on exchange and consume data.
Key Features:
- Centrally manage member access.
- Build a community for data sharing as per organization needs.
- Scale effortlessly as the number of consumers grows.
Use Case: Best for large-scale data sharing initiatives involving multiple stakeholders.
- Data share across cloud/region
Cross cloud/region data can be shared across cloud using replication.
Key Features:
- Snowflake supports cross region/cloud sharing for AWS, GCP and AZURE vendors.
- Providers must create a dataset for each region to facilitate sharing with multiple consumers ensuring alignment with preferred cloud vendor.
- Enables sharing of data according to the consumer’s preferred cloud vendor.
Use Case: Useful when provider and consumer utilize different cloud vendors.
Benefits of Snowflake Share
- Instantaneous Updates: Consumers always access the latest source data.
- No Redundancy: No need to duplicate data, reducing storage and cost overhead.
- Simplified Collaboration: Streamlined sharing processes with zero ETL effort.
- Revenue Opportunities: Providers can monetize data through the Marketplace.
- Scalability: Snowflake’s architecture supports growing data sharing needs effortlessly.
- Architectural and integration compatibility: Snowflake share aligns with modern data fabric architectures, minimizing data movement and streamlining workflows.
Figure 1: Snowflake Data Sharing
Conclusion
Snowflake’s Share feature is a game-changer, offering a seamless, efficient, and secure way to share data both within and beyond organizational boundaries. Whether you’re a data provider aiming to monetize your assets or a consumer seeking consistent, real-time access, Snowflake offers the tools to make data sharing a breeze. In modern data architectures that prioritize minimal data movement, Snowflake Share proves to be an indispensable feature. It supports the seamless integration of data fabrics, simplifying sharing and collaboration in ways traditional methods cannot match.
About Authors
Omkar Prabhu – Omkar serves as the Center Head, managing the Goa location at Zimetrics. He brings extensive industry experience in building scalable applications and data solutions. Beyond his primary role, Omkar contributes as a Data Architect, where he excels in implementing multiple data lake solutions using the Snowflake ecosystem, showcasing his expertise in modern data architectures.
Satagonda Jatrate – Satagonda, a Software Engineer at Zimetrics, specializes in Snowflake, focusing on ETL pipelines, data sharing, and transformation. His proficiency drives efficient workflows and delivers actionable insights, empowering data-driven decision-making.