With this release candidate we want to highlight the next two features of the upcoming release. Data Masking and Time-To-Live indices (TTL) can come in very handy for developers when it comes to compliance with data privacy regulations like GDPR or the upcoming Consumer Privacy Act of California.
As always: Release candidates are for testing purposes only and should not be used for production! Before upgrading, please make a backup of your system.
Let’s dive into RC2.
No matter if you want to comply with the “Right to be forgotten” of GDPR or just do not want to think about deleting expired sessions or old statistics, TTL comes in quite handy.
This new index type lets you automatically expire documents in a collection. The index can be configured to delete documents on a specific date/time or after a certain period of time. Using various startup parameters, you can also configure e.g. the frequency of the background job deleting expired documents. If you want to give TTL indices a try, check out the Time-To-Live tutorial.
In many cases, it is either convenient or very necessary to use production data for development, issue investigation or testing purposes. But internal compliance, GDPR regulations and just common sense might prohibit the use of personal user data outside of a secured production environment. Data Masking solves this dilemma.
The new data masking feature of arangodump provides a convenient way to extract production data but mask critical information that should not be visible. This includes names, birthdays, credit card numbers, addresses, emails or phone numbers. Within the Community Edition of ArangoDB 3.5, you can mask any attribute value with a random string value.
Sometimes it can be important for your purpose to preserve the structure of the values (e.g. birthday or credit card number). For these cases, the arangodump of the Enterprise Edition comes with special masking functions to obfuscate certain values with a random value of the same structure.
If you want to start masking your data, find the Data Masking tutorial in our Training center.
Hope these two new features are useful for you and your projects. If you have any feedback to the RC, please let us know via GitHub and specify the RC version you are using.
Known issues of RC2:
- For everybody who has a view of type arangosearch created and wants to upgrade ArangoDB from 3.4.x to RC2 of ArangoDB 3.5, we recommend to delete the view in 3.4.x, then upgrade to RC2 and create the view anew.
Other known issues can be found in the devel docs.