Static Data Masking vs. Dynamic Data Masking: What’s the Best Approach?

Static data masking vs. dynamic data masking: which is better at data masking?

Spoiler alert for this blog: static data masking is the best approach in non-production environments!

What Is Static Data Masking?

Static data masking is the process of replacing sensitive values with fictitious, yet realistic equivalents. With static data masking, data is changed and written to the data source. There is no path back to the original data. 

For example, a SSN of 123-45-1890 is changed to 045-12-3345. Static data masking is ideal for producing test and analytic data sets. It is not used on production data.

Find out why static data masking is the best approach in our on-demand webinar: Five Approaches for Protecting DevOps Test Data.

What Is Dynamic Data Masking?

Dynamic data masking is the process of replacing sensitive data in use rather than at the source. With dynamic data masking, data is changed during delivery, or presentation of the data. The original data is not changed. 

For example, a customer service rep might see XXX-XX-0341 on their screen, but back in the database, the full SSN is still intact. Dynamic data masking is ideal for production break-fix or other use cases where production data is required. It is not used to produce test or analytic data sets.

Static Data Masking vs. Dynamic Data Masking

The main difference between static data masking and dynamic data masking is this: static masks the database itself while dynamic keeps original data and shows users redacted data.   

How Data Is Masked: Static vs. Dynamic

In static data masking, the original data is replaced by masked data before the data is copied to a less secure non-production (non-live) database. Masked data in this context is data that cannot be re-transformed back to its unmasked value. There is no path back to the original value. For example, the name “David” becomes “Bob.”

In dynamic data masking, the original data remains unchanged in the production database, but the data served to the user is redacted. For example, the name “David” becomes “XXXXX”. 

Who Should Use Static vs. Dynamic

Static data masking is best suited for:

·      Software development and testing.

·      Third-party vendor access.

·      Business continuity testing.

·      Training and education.

·      Analytics.

·      Scenarios where the overhead associated with dynamic is not acceptable.

Dynamic data masking is best suited for read-only applications. There are other use cases where dynamic could be used, but it may not be ideal (such as in analytics environments).

Best Data Protection: Static vs. Dynamic

If a database is breached, only static data masking will protect sensitive data from compromise. That’s because the sensitive data in the database itself has been replaced with irreversible fictitious values.

If the database was protected with dynamic data masking, the breach will result in the compromise of any sensitive data. The database still contains sensitive data.

Especially when there is sensitive data sprawl, it’s critical to eliminate the risks. Typically, non-production environments do not have the extensive auditing and security controls that are present in production environments.

In addition, many more users have access to non-production systems. For these reasons, it is imperative to protect non-production environments by eliminating the sensitive data they contain.

The 2024 State of Data Compliance and Security Report

66% of organizations we surveyed are using static data masking to protect non-production data. Discover insights from 250 global leaders around sensitive data, compliance, masking, AI, and more.

Get the Data Compliance Report >>

Benefits of Static Data Masking Over Dynamic Data Masking

There are five key benefits of static data masking over dynamic data masking. 

Zero Trust and Data Security

One component of zero trust is complying with privacy laws by masking PII and PHI. Static data masking delivers on zero trust by masking that data before it goes in a non-production environment.

Dynamic data masking is less secure in non-production environments. The real-time nature of dynamic data can be a vulnerability. 

Referential Integrity

Application development and testing teams need production-like copies of the production database for their testing. And sensitive data in those databases needs to masked while preserving referential integrity.

Static data masking is the best way to ensure referential integrity across tables, schemas, databases, and cloud environments.

No Overhead Caused by Agents

Dynamic data masking has overhead associated with it — every time a query is executed, the access rights of the user need to be established, and the necessary masking of specific elements must take place. 

With static data masking, the changes to the data have already been persisted, so that there is no overhead or change to the way data is delivered to requesters.

No Agents

Dynamic data masking often requires an agent, different JDBC driver, or a proxy service in between the data and the data requester. As a result, it can be very challenging to implement dynamic data masking across all types of data sources present in an enterprise. 

With static data masking, no agents or proxy services are required.

Works on Mainframe and File Data

Static data masking can be applied to data sources that include mainframe and file data.  Mainframe and file data is difficult and, in some cases, impossible to present via a dynamic data masking layer. This is due to security reasons as well as logistical reasons. 

How Static Data Masking Works with Delphix

Delphix static data masking is a powerful way to protect sensitive data in non-production environments.

With Delphix, you can automatically discover sensitive data and mask it to provide production-like data. This is done using a rich library of pre-built and customizable algorithms. As a result, you’ll be able to mask everything from names and social security numbers to images and text fields.

Delphix static data masking can be applied to various sources. This includes databases — such as SQL Server and Oracle — and analytical sources — such as Snowflake and Databricks.

By leveraging Delphix static data masking, you’ll ensure data security, utility, and referential integrity across data sources.

2024 Masking Insights: Revealed and Analyzed by the Delphix Experts

How are you protecting sensitive data in non-production environments? In our recent State of Data Compliance and Security Report, 66% cited use of static data masking. Discover other masking insights, including how to use masking for data compliance — without making trade-offs for quality or speed!

Join the live webinar on October 2.

Register now for masking insights >>

Delphix Static Data Masking in Practice

Here are some examples of Delphix static data masking in practice to achieve speed, quality, and compliance. 

Worldpay from FIS relies on Delphix to automatically mask sensitive data. As a financial services organization, they have tons of sensitive data that customers trust will be held securely. By utilizing Delphix, they were able to mask data and automate test data management. As a result, they achieved 7x faster refreshes for test environments and reduced test data storage by 75–80%. 

Another financial services organization — Boeing Employees Credit Union (BECU) — saw similar results. By masking sensitive data with Delphix, they ensured consistency and reliability. They also achieved speed — in just 15 hours, they masked 680 million rows of data.

In the insurance industry, Delta Dental uses Delphix to mask data and deliver virtual data copies to a team of 200 developers in minutes. And they can trust that PII and PHI are masked before the data is replicated. 

For Proximus, a telecommunications company, leveraging Delphix led to a 97% reduction in data masking time, as well as 85% reduction in non-production data storage. Plus, Delphix reduced wait times for testing teams, enabling them to move faster. 

Get Started with the Delphix Compliance Solution

With Delphix, you get static data masking — and more. You get compliance solutions that protects your sensitive data in non-production environments while accelerating innovation. Whether your environment is software development, testing, analytics, or AI, Delphix is here to help you achieve compliance, speed, and quality. No trade-offs necessary.

Compliant Data

Static data masking is often a requirement of regulations like GDPR and HIPAA. Delphix Continuous Compliance satisfies those requirements. You’ll be able to detect PII/PHI data and mask data using a rich library of pre-built and customizable algorithms.

 The end result? Compliant data you can count on.

Speed at Enterprise Scale

Compliance doesn’t need to cost you speed. With Delphix, you can automate and accelerate the delivery of masked test data at enterprise scale. In addition to static data masking workflows, you’ll gain sensitive data discovery. And you’ll be able to automate the delivery of masked data to dev, test, analytics, and AI.

The end result? Faster development speeds that enable your business to gain a competitive edge.

Software Quality

Static data masking with Delphix means you deliver realistic, production-like test data. You’ll preserve referential integrity across the enterprise data estate to ensure that complex tests succeed. And you’ll rapidly deliver secure, high-quality data to downstream teams, when and where they need it. That means they can shift left and catch defects earlier.

The end result? High-quality tests results and overall better-quality software.

See Delphix in Action

Our team of masking and compliance experts is here to help you. Request your demo today to explore Delphix static data masking, compliance, and beyond.

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