Make Data Compliance Easier Across Your Enterprise

If we go back to the launch of our masking technology just a few years ago, virtually all customer demand was for Oracle and Microsoft SQL Server since our primary business proposition was driven by virtualizing copies of data via self-service for those specific databases. Over the years though, this has dramatically changed.

As more companies have taken on digital transformation projects, safeguarding their data against cyber threats and complying with the ever-evolving landscape of privacy regulations have become just as important.

Organizations today embrace a model that allows them to choose a database based on an application’s needs. For example, most cloud-native applications require a combination of NoSQL databases and object storage for scalability—prompting enterprise organizations to adopt up to half a dozen databases or more at any given time. Many companies are also using SaaS applications that require data compliance in all environments.

Delphix masking essentially takes an automated approach to protecting non-production environments by replacing sensitive values with fictitious, yet realistic equivalents while preserving referential integrity within and across sources. Sensitive data can also be tokenized and reversed.

Extending Compliance to Modern Data Stores

We’ve deliberately added support for the popular data sources from MySQL and PostgreSQL to XML files. But as the number of data sources continues to grow at an accelerated rate, we wanted to enable the broader ecosystem and bring data masking to the ever-growing number of sources.

This is where extensible connectors come into play. It allows our customers and partners to upload third-party commercial and open source drivers and extend masking to almost any data source type, such as MongoDB Atlas, Salesforce, HANA, and Snowflake. You can learn more about how to install and manage extended connectors in the Delphix documentation center.

Masking More Data Than Ever Before

Extensible connectors only solve half of this challenge. The other half is about making it possible to protect all modern types of data using extensible algorithms. The new algorithm SDK framework enables our customers and partners to create and share new masking algorithms themselves.

The SDK enables users to develop algorithm extensions using industry-standard Java language and tools—without the detailed knowledge about the product previously required to write custom algorithms. Users can create the following types of algorithms to mask data:

• String

• Date

• Numeric

• Binary (images)

For example, if you wanted to take ‘Andy’ and mask it to ‘Jason,’ here’s what it would look like:

**
  * Mask String object
  * @param input The String object to be masked. This method should handle null inputs
  * @return Returns the masked value.
  */
  @Override
  public String mask (@Nullable String input) {
          // TODO: change the default implementation
          return “Jason”;
}

/**
  * Get the recommended name of this Algorithm.
  * @return The name of this algorithm
  */
  @Override
  public String getName() {
          // TODO: Change this if you’d like to name 
          // your algorithm differently from the Java class.
          return “TheJasonAlgorithm”;
 }

Extensible Connectors + Extensible Algorithms: A Winning Combination

Data is heavy, complex, and filled with security and privacy risk. Delphix’s extensible connectors and algorithm SDK together empower application development teams to mask sensitive data from any data source type and control how data is anonymized. With these new capabilities, enterprises have the flexibility to transform data as they see fit and gain the peace of mind from knowing more of their data is secure. Dive deeper in this demo.

Download this whitepaper to learn how to deploy and customize masking algorithm frameworks and integrate data masking into critical business workflows via APIs.