Why data sharing eliminates data copies in Snowflake - Why It Works This Way

Overview - Why data sharing eliminates data copies

What is it?

Data sharing is a way to let different people or systems use the same data without making extra copies. Instead of copying data files or databases, data sharing allows direct access to the original data. This saves space and keeps data consistent for everyone who uses it.

Why it matters

Without data sharing, every team or system would need its own copy of data. This wastes storage, causes confusion when copies get out of sync, and slows down updates. Data sharing solves these problems by letting everyone work with one true version of the data, making work faster and more reliable.

Where it fits

Before learning data sharing, you should understand basic cloud storage and databases. After this, you can explore advanced data governance, security controls, and multi-cloud data architectures.

Mental Model

Core Idea

Data sharing lets multiple users access the same data directly, avoiding extra copies and keeping data consistent.

Think of it like...

Imagine a library where many people read the same book on-site instead of each person buying their own copy. Everyone sees the same pages, and the library only needs one book.

┌───────────────┐       ┌───────────────┐
│   Data Owner  │──────▶│ Shared Data    │
└───────────────┘       └───────────────┘
                             ▲      ▲
                             │      │
                  ┌──────────┘      └──────────┐
          ┌───────────────┐          ┌───────────────┐
          │ Consumer A    │          │ Consumer B    │
          └───────────────┘          └───────────────┘

Build-Up - 6 Steps

1

Foundation

Understanding Data Copies

Concept: Learn what it means to copy data and why copies exist.

When teams work with data, they often make copies to have their own version. For example, a sales team might copy customer data to analyze it separately. Each copy takes storage space and can become outdated if not updated.

Result

You see that copying data creates multiple versions that need extra space and management.

Understanding data copies helps you see why managing many copies is inefficient and error-prone.

2

Foundation

Basics of Data Sharing

Concept: Introduce the idea of sharing data without copying it.

Data sharing means giving others permission to use your data directly. Instead of sending a copy, you let them access the original data where it lives. This way, everyone sees the same up-to-date information.

Result

You realize data sharing avoids extra copies and keeps data consistent.

Knowing that data sharing is about access, not duplication, sets the stage for deeper understanding.

3

Intermediate

How Snowflake Enables Data Sharing

🤔Before reading on: do you think Snowflake copies data when sharing or just grants access? Commit to your answer.

Concept: Snowflake shares data by granting access to the original data without copying it.

In Snowflake, data sharing works by creating a 'share' object that points to the original data. Consumers use this share to query data directly. Snowflake manages permissions and access controls, so no data is duplicated during sharing.

Result

You understand that Snowflake's data sharing is efficient and secure, with no extra storage used.

Knowing Snowflake shares pointers, not copies, explains how it saves storage and keeps data fresh.

4

Intermediate

Benefits of Eliminating Data Copies

🤔Before reading on: do you think eliminating copies only saves space, or does it affect data accuracy too? Commit to your answer.

Concept: Removing data copies saves storage and ensures everyone sees the same accurate data.

When data copies are eliminated, updates happen once and are visible to all users immediately. This reduces errors from outdated copies and lowers costs by using less storage. It also simplifies data governance and compliance.

Result

You see that eliminating copies improves data quality and reduces operational overhead.

Understanding these benefits shows why data sharing is a game-changer for organizations.

5

Advanced

Security and Access Control in Data Sharing

🤔Before reading on: do you think sharing data without copies risks exposing all data, or can access be controlled? Commit to your answer.

Concept: Data sharing includes strict controls so users only see what they are allowed to.

Snowflake lets data owners define exactly which tables or views to share and who can access them. Consumers cannot change the data or see anything outside the share. This keeps data secure while enabling collaboration.

Result

You understand that data sharing balances openness with security.

Knowing how access controls work prevents fears about data leaks and builds trust in sharing.

6

Expert

Performance and Cost Implications of Data Sharing

🤔Before reading on: do you think data sharing always reduces costs, or can it sometimes increase them? Commit to your answer.

Concept: Data sharing can reduce storage costs but may affect compute costs depending on usage patterns.

While data sharing avoids extra storage, each consumer's queries use compute resources. If many consumers run heavy queries, compute costs can rise. Snowflake separates storage and compute, so owners and consumers can manage costs independently.

Result

You realize data sharing optimizes storage but requires monitoring compute usage.

Understanding cost trade-offs helps design efficient data sharing strategies in production.

Under the Hood

Snowflake stores data centrally in cloud storage. When data is shared, Snowflake creates metadata objects called shares that reference the original data objects. Consumers access data through these shares, which enforce permissions and provide a virtual view without duplicating data. Queries from consumers run on their own compute resources but read the shared data directly.

Why designed this way?

This design avoids costly data duplication and synchronization problems. By separating storage from compute and using metadata pointers, Snowflake enables scalable, secure sharing. Alternatives like copying data were slower, more expensive, and risked data inconsistency.

┌───────────────┐       ┌───────────────┐       ┌───────────────┐
│ Cloud Storage │◀──────│   Snowflake   │──────▶│   Consumer    │
│  (Data)      │       │   Metadata    │       │  Compute      │
└───────────────┘       └───────────────┘       └───────────────┘
        ▲                      ▲                        ▲
        │                      │                        │
   Original Data           Share Object             Query Access

Myth Busters - 4 Common Misconceptions

Quick: Does data sharing in Snowflake create a full copy of the data for each consumer? Commit to yes or no.

Common Belief: Data sharing means copying data to each consumer's account.

Reality: Snowflake shares data by granting access to the original data without copying it.

Why it matters: Believing copies are made leads to overestimating storage needs and misunderstanding cost benefits.

Quick: Can consumers modify shared data directly? Commit to yes or no.

Common Belief: Consumers can change the shared data since they have access.

Reality: Consumers can only read shared data; they cannot modify it.

Why it matters: Thinking consumers can change data causes unnecessary fears about data integrity.

Quick: Does data sharing automatically reduce all costs? Commit to yes or no.

Common Belief: Data sharing always lowers all costs including compute.

Reality: Data sharing reduces storage costs but compute costs depend on consumer query usage.

Why it matters: Assuming all costs drop can lead to unexpected bills if query loads increase.

Quick: Is data sharing only useful within the same organization? Commit to yes or no.

Common Belief: Data sharing is only for internal teams, not external partners.

Reality: Snowflake supports secure data sharing across different organizations and accounts.

Why it matters: Limiting data sharing to internal use misses opportunities for collaboration and business growth.

Expert Zone

1

Data shares are read-only and cannot be altered by consumers, ensuring data integrity.

2

Snowflake's separation of storage and compute allows independent scaling and cost control for data owners and consumers.

3

Data sharing metadata objects can be versioned and managed to control data visibility over time.

When NOT to use

Avoid data sharing when consumers require write access or data transformation before use. In such cases, data replication or ETL pipelines are better. Also, if consumers need offline access without network connectivity, copies are necessary.

Production Patterns

Enterprises use Snowflake data sharing to provide real-time data feeds to partners, enable cross-department analytics without data duplication, and build data marketplaces where multiple consumers access curated datasets securely.

Connections

Content Delivery Networks (CDNs)

Both optimize resource use by sharing access rather than duplicating content.

Understanding how CDNs serve the same files to many users without copying helps grasp how data sharing avoids duplication.

Library Book Lending

Data sharing is like lending a book to many readers without buying multiple copies.

This connection shows how sharing a single resource efficiently benefits many users.

Network File Systems (NFS)

NFS allows multiple computers to access the same files over a network, similar to data sharing.

Knowing NFS helps understand how shared access to data can be managed securely and efficiently.

Common Pitfalls

#1 Assuming data sharing copies data and thus provisioning extra storage unnecessarily.

Wrong approach:

CREATE DATABASE copy_db CLONE original_db; -- thinking this is data sharing

Correct approach:

CREATE SHARE my_share; GRANT USAGE ON DATABASE original_db TO SHARE my_share;

Root cause:

Confusing cloning or copying databases with Snowflake's data sharing feature.

#2 Granting broad access in shares without restricting sensitive data.

Wrong approach:

GRANT SELECT ON ALL TABLES IN SCHEMA sensitive_schema TO SHARE my_share;

Correct approach:

GRANT SELECT ON TABLE public_data TO SHARE my_share; -- exclude sensitive_schema

Root cause:

Not understanding that shares must be carefully scoped to protect data privacy.

#3 Expecting consumers to have write permissions on shared data.

Wrong approach:

Consumers trying to run INSERT or UPDATE on shared tables.

Correct approach:

Consumers use SELECT queries only; data owners manage writes.

Root cause:

Misunderstanding that shared data is read-only for consumers.

Key Takeaways

Data sharing allows multiple users to access the same data directly without making copies.

Eliminating data copies saves storage, reduces errors, and keeps data consistent for all users.

Snowflake implements data sharing by creating metadata shares that point to original data securely.

Data sharing balances openness with strict access controls to protect data privacy and integrity.

While storage costs drop with data sharing, compute costs depend on how consumers query the data.