Enterprise Business Data Share
Rox Data Share vs Warehouse Native for Enterprise Business Systems Data
Introduction
At Rox, we integrate public and private data into a single, real-time view, enabling sellers to make informed decisions and drive better outcomes. A critical part of this process involves securely accessing and working with private data from enterprise companies. In this post, we explain how Rox achieves this while maintaining a secure and compliant architecture.
Data Sharing with Rox
Rox supports both the data share approach and the warehouse native approach.
The Data Share Approach
The Data Share approach enables organizations to share data directly from a source system, such as a data warehouse or a Lakehouse, without the need to move or duplicate it.
For example, Rox works with Snowflake, Redshift, and BigQuery’s native data-sharing features to access enterprise data without the need for direct data copying.
Key Features of Data Shares
Real-Time Access: Data consumers access data directly from the provider’s infrastructure.
No Data Duplication: Data remains stored in the provider’s environment.
Dynamic Updates: Any updates made to the shared data are immediately available to consumers.
Benefits
Cost Efficiency: Eliminates the need for duplicating or transferring data.
Consistency: Consumers access the most up-to-date version of the data.
Security: Fine-grained sharing controls prevent unauthorized access while data remains within the provider’s control.
Simplified Collaboration: Ideal for sharing data across teams, departments, or external partners without complex pipelines.
Limitations
Dependency on Source System: Consumers depend on the performance and uptime of the provider’s infrastructure.
Limited Transformations: Shared data may need further processing on the consumer side.
Example: Rox <> Redshift
Here’s an example of how to share data from Redshift with Rox:
Producer Cluster Setup (Customer-Side):
The customer creates a Producer Cluster where their data resides, ensuring it meets requirements like encryption and supported RA3 instance types.
A data share is created using SQL commands or via the Redshift console.
Specific schemas and tables (e.g., public.salesforce) are added to the data share, granting access to Rox’s AWS account.
Consumer Cluster Setup (Rox-Side):
Rox creates a Consumer Cluster, dedicated to the customer, with encryption enabled.
The customer-authorized data share becomes available for association in this cluster.
Data Share Association:
Once authorized by the customer, the data share is associated with Rox’s Consumer Cluster via the Redshift console.
By leveraging native Redshift data sharing, Rox provides a seamless, secure method for integrating enterprise data.
Warehouse-Native Approach
The Warehouse Native approach involves integrating all data directly into a single data warehouse environment where processing, transformations, and analysis occur. Rox uses Snowflake to store (in customer specific isolated databases) and compute.
Key Features of Warehouse Native Approach
Centralized Storage: Data from various sources is ingested, transformed, and stored in the warehouse.
Comprehensive Processing: Supports in-warehouse transformations using SQL or other tools.
Unified Ecosystem: All analysis and processing are performed within the warehouse.
Benefits
Performance Optimization: Querying and transformations are optimized within the warehouse environment.
Data Availability: All integrated data is readily accessible for analysis or modeling.
Compatibility with BI Tools: Works seamlessly with tools like Tableau, Looker, or Power BI.
Limitations
High Costs: Ingesting and storing large volumes of data can become expensive.
Latency: Data may not always be real-time, depending on ETL/ELT pipeline schedules.
Data Duplication Risks: Involves copying data from source systems into the warehouse.
Example: Rox <> Fivetran <> Snowflake
Rox leverages Powered by Fivetran to seamlessly integrate customer data into dedicated databases in our warehouse.
Using Fivetran’s REST API, Rox programmatically sets up connectors for CRM systems or other SaaS applications, streamlining data ingestion without manual intervention. This approach enables real-time synchronization with source systems, ensuring data consistency and reliability.
Rox creates a Fivetran group linked to the destination and configure connectors with source-specific parameters.
Rox manages the sync schedules.
The ability to manage these programmatically allows Rox to onboard enterprise data sources efficiently, reducing operational overhead while maintaining high scalability and compliance with data security standards.
Comparison Table
| Feature | Data Share | Warehouse Native |
|---|---|---|
Data Movement | No data movement; real-time sharing | Requires data ingestion into the warehouse |
Cost | Lower (no duplication or storage costs) | Higher (storage and processing costs) |
Data Freshness | Real-time | Dependent on ETL/ELT schedules |
Security | Data stays with the provider; granular control | Centralized security in the warehouse |
Transformation | Minimal (on consumer side) | Extensive capabilities |
Use Case Fit | Cross-organization or external sharing | Internal, large-scale processing |
Choosing the Right Approach
When to Use Data Share:
Real-time data collaboration is critical.
Sharing data across teams or external partners without duplication.
You want to reduce storage costs and ensure data consistency.
When to Use Warehouse Native:
Your workflows require complex data transformations.
A centralized repository for all data assets is essential.
Analytics and reporting are tightly coupled to the warehouse.
The Hybrid Approach
For enterprises with more complex requirements, Rox uses a hybrid model.
Rox combines native data sharing with selective data ingestion.
It allows for the flexibility to choose what data stays in the enterprise warehouse versus what needs to be ingested into a secure Rox-managed environment.
This model offers the best of both worlds: native integration with the enterprise’s systems and the flexibility to handle edge cases or compute-heavy tasks efficiently.
Ease of Integration
Rox is designed to simplify setup and integration:
Using our admin UI, enterprise customers can connect their data sources in minutes.
The process requires minimal technical effort, ensuring rapid onboarding without compromising security or compliance.
Security and Compliance
Security is a foundational pillar at Rox, and we adhere to stringent security and compliance standards.
Data Protection: Access controls, encryption, and audit trails are implemented across all systems.
Compliance: Rox meets industry-specific regulations, ensuring adherence to enterprise requirements like GDPR, CCPA, and SOC 2.
Isolation: Each enterprise’s data is handled in dedicated environments, ensuring operational isolation and data confidentiality.
Conclusion
Rox’s architecture enables secure, scalable, and compliant access to enterprise data, whether through native data sharing, warehouse-native ingestion, or hybrid approaches. By offering flexibility and focusing on ease of integration, Rox empowers enterprises to unlock the full potential of their data while meeting their most demanding security and compliance requirements.
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