Hyperscale Compliance Overview
Hyperscale Compliance from Perforce Delphix is optimized for protecting large-scale data sources like Oracle, SQL Server, and Snowflake to ensure compliance without bottlenecking critical innovation. It masks 10s of terabytes at speeds starting at 2 billion records/hour, while retaining data quality and referential integrity across your estate.
The Perforce Delphix Difference: Hyperscale Compliance
Key Capabilities of Hyperscale Compliance
Protect sensitive data, like PII and PHI, in development, analytics, and AI. Mask large-scale sources like Oracle, SQL Server, and Snowflake.
- Ensure regulatory compliance with data privacy regulations (GDPR, HIPAA, CCPA, etc.) and prevent theft.
- Discover and irreversibly mask sensitive data with pre-built and customizable algorithms.
- Securely share data for analytics, AI, and software development globally — including with third parties and offshore collaborators.
Mask 10s of terabytes of data in hours not weeks, so you can speed up innovation securely.
- Meet SLAs for protecting mission-critical, large-scale, non-production data sources, on-premises or in cloud.
- Horizontally scale and automate masking jobs to rapidly deliver compliant data to downstream consumers who are developing software, analytics, or AI.
- Mask rapidly at speeds starting at 2 billion records/hour to protect your most challenging and critical data sources.
Deliver high-quality, compliant data to enable quality software, analytics, and AI.
- Replace sensitive data with fictitious, yet realistic values reflecting complex enterprise data and its relationships to ensure accurate development and testing and retain analytical meaning.
- Consistently discover and mask sensitive data with referential integrity across cloud and on-premises sources, to enable end-to-end integration testing, uniform policies, and analytical accuracy.
- Encourage adoption and avoid exception requests by providing quality compliant data, trusted by downstream teams and blessed by InfoSec.
How Hyperscale Compliance Works
Discover Sensitive Data
Automatically profile and discover sensitive data like PII/PHI within large-scale data sources. Eliminate the risk of missed data exposures in large data volumes.
- Apply pre-built and custom profiles per regulations and policies
- Consistently profile across on premises and cloud sources
- Automatically match profiles to masking algorithms
Scale Horizontally
Substantially reduce the time to mask large-scale databases by using an automated, parallel processing masking workflow.
- Bulk-download all data that needs to be masked and send it to the Hyperscale Orchestrator for processing
- Split the data into digestible file chunks and divvy them out to Continuous Compliance engines
- Mask the jobs in parallel, re-assemble the masked data by the Orchestrator and bulk-load compliant data into the target system
Mask with Quality and Referential Integrity
Replace sensitive data with realistic yet fictitious data that honors referential integrity. Protect sensitive data per regulation and corporate policies.
- Deliver production-like, compliant data, reflecting enterprise complexity and preserving data utility
- Mask with referential integrity, reflecting compliance policies consistently across on-premises and cloud sources
- Deliver quality, compliant data that downstream consumers can trust. Ensure adoption and avoid compliance exception requests
Deploy On-Premises or In Cloud
Benefit from the architectural flexibility to deploy in your cloud of choice or on-premises.
- In your own data center
- In private cloud
- In your preferred public cloud including AWS and Azure (IaaS model)
Connectors For YOUR Sources
Hyperscale Compliance includes connectors to protect large scale sources, including transactional and analytical systems:
Delphix Hyperscale Compliance FAQs
Learn more about Delphix Hyperscale Compliance.
Hyperscale Compliance masks large-scale datasets at unparalleled speeds, expediting multi-week masking jobs to hours, to meet business-critical SLAs for DevOps, analytics, and AI. It is optimized for masking 10s of terabytes at speeds starting at 2 billion records per hour.
Hyperscale Compliance substantially reduces the time to mask large databases using an automated, parallel processing masking workflow. It splits large amounts of data into digestible file chunks. These are then masked in parallel across multiple Delphix masking engines, re-assembled, and bulk-loaded as compliant data into to the target system.
Hyperscale Compliance is optimized for fast masking of datasets larger than 10 terabytes using parallel processing while Delphix Continuous Compliance is a viable and well-performant option for datasets smaller than 10 terabytes. Continuous Compliance uses JDBC drivers to deliver masking as a transactional read-write operation. Both solutions utilize similar sensitive data discovery profilers and data masking algorithms for consistent discovery and masking with referential integrity across enterprise sources.
Yes, Hyperscale Compliance offers masking for Snowflake, whether it is running on AWS or on Microsoft Azure. Unlike native Snowflake masking, Hyperscale masking irreversibly masks data to avoid data reidentification risks and offers referential integrity between Snowflake masked data and other enterprise data sources. This ensures consistent adherence to enterprise policies and avoid errors in integration testing or analytics.
Have a large-scale Oracle or SQL Server dataset (larger than 10 terabytes)? Is it tied to a mission-critical application where masking SLAs of hours (instead of weeks or months) are expected? Then you should use Hyperscale.
Need to mask Snowflake but are struggling with security, masking speed, or quality challenges? Are you lacking referential integrity between Snowflake and other enterprise data sources? Hyperscale is a great fit for that, too!
Make Large-Scale Masking Easier With Delphix Hyperscale Compliance
Get in touch with our team of masking and compliance experts. We’ll walk you through how Hyperscale Compliance will help you:
- Speed up compliance for large-scale datasets.
- Mask 10 TB+ in hours, not weeks, at a speed of 2 billion rows / hour.
- Deliver quality, compliant data with referential integrity.