In a world where AI, personalization, and fast-moving tech rule, granular data insights are the competitive advantage. But to actually tap into them – confidently and compliantly – your access controls need to be equally granular.
In this guide, we will explore how row-level security works and the benefits it provides. You’ll see how teams across industries – from healthcare to e-commerce – use row-level security to drive business, and how attribute-based access control (ABAC) helps take the complexity out of the equation, so you can de-risk your data and get value from it faster.
What Is Row-Level Security?
Row-level security is a data access control mechanism that restricts access to specific rows within a database table based on user permissions. It ensures that users are only able to interact with the data they are authorized to access.
In contrast to coarse-grained approaches such as database-, table-, and column-level security, row-level security allows you to control data access down to the exact row – making it a much more precise option. As sensitive data use grows increasingly common, this type of fine-grained access control is crucial in order to derive value from data while avoiding the costly fines and legal penalties that come from misusing it.
How Does Row-Level Security Work?
Row-level security manages access to individual records within a table based on user permissions, such as role, department, and location, among others. When a user queries a table, row-level security controls automatically filter out the rows they do not have permission to see, leaving only the rows that they are authorized to access and use.
Row-level security is particularly useful in industries that rely heavily on data sharing, such as healthcare and life sciences, public sector, and financial services. Restricting row access allows you to mask specific and potentially sensitive data – including personally identifiable information (PII) and protected health information (PHI) – but still collaborate on other data in the table. Likewise, if two different user roles need to leverage the same table, row- and column-level security allows them to do so.
Example: Row-Level Security in Action
Let’s say you work in a research hospital and are performing a clinical trial to develop a new vaccine. You need to track biomarkers from trial participants over time to assess variations in the test group versus the control group, which may indicate that the vaccine causes side effects. Your database table may look like this:
| Patient Name | Patient ID | Patient Group | Age | Heart Rate (bpm) | Blood Pressure (mm/Hg) | Vaccination Status |
|---|---|---|---|---|---|---|
| John Smith | 001234 | 2 | 45 | 72 | 120/80 | true |
| Jane Doe | 001235 | 1 | 37 | 75 | 118/76 | false |
| Alice Brown | 001236 | 1 | 29 | 68 | 122/78 | true |
| Bob Johnson | 001237 | 2 | 50 | 80 | 130/85 | false |
| Carol White | 001238 | 2 | 42 | 74 | 115/75 | true |
Now, let’s say you work for the pharmaceutical company that’s funding the trial. You want to know what percentage of the trial participants have received the vaccination at various points throughout the trial. This is easily done by creating a policy that masks all columns except the “Vaccinated” column for users in the Pharmaceutical Company group:
| Patient Name | Patient ID | Patient Group | Age | Heart Rate (bpm) | Blood Pressure (mm/Hg) | Vaccination Status |
|---|---|---|---|---|---|---|
| ***** | ***** | ***** | ***** | ***** | ***** | true |
| ***** | ***** | ***** | ***** | ***** | ***** | false |
| ***** | ***** | ***** | ***** | ***** | ***** | true |
| ***** | ***** | ***** | ***** | ***** | ***** | false |
| ***** | ***** | ***** | ***** | ***** | ***** | true |
Now, let’s say you are a healthcare professional administering care for a small group of the trial participants. You’re responsible for recording and updating charts with Group 1 patients’ biomarker information, so you need to be able to see every column except “Vaccinated” for your patients. Based on a policy that masks rows except those containing data tagged “Patient Biomarkers” for Patient Group 1, your table may look like this:
| Patient Name | Patient ID | Patient Group | Age | Heart Rate (bpm) | Blood Pressure (mm/Hg) | Vaccination Status |
|---|---|---|---|---|---|---|
| ***** | ***** | ***** | ***** | ***** | ***** | true |
| Jane Doe | 001235 | 1 | 37 | 75 | 118/76 | ***** |
| Alice Brown | 001236 | 1 | 29 | 68 | 122/78 | ***** |
| ***** | ***** | ***** | ***** | ***** | ***** | false |
| ***** | ***** | ***** | ***** | ***** | ***** | true |
Combining row-level security with column-level security allows users with different roles and access needs – such as the pharmaceutical company representative and the healthcare administrator – to leverage the same data sets, while ensuring that each is only able to see and use the data to which they are authorized.
Benefits of Row-Level Security
The key benefit of row-level security is that it provides granular access control while maximizing data utilization. This is an important distinction from legacy, coarse-grained access control methods, which locked down broad swaths of data and halted forward momentum. Paired with a data security platform that supports ABAC, you’re able to easily enforce fine-grained policies, enable self-service data access, improve collaboration, and seamlessly integrate data security into modern data workflows.
Here are four reasons to implement row-level security:
Enhanced Data Security
Row-level security allows database administrators or data owners to control access to sensitive information at a highly granular level. This method protects the confidentiality and integrity of sensitive data by ensuring users only have access to the specific data they are authorized to view.
Improved Compliance
Compliance with compliance laws and regulations such as GDPR, HIPAA, and CPRA has become more challenging as sensitive data use increases, and more teams handle more data more regularly.
For example, certain regulations – including those listed above – prevent data users from viewing sensitive data without an explicit, authorized purpose. Row-level security enforces access controls to filter out protected information, helping meet your compliance objectives without cumbersome, manual processes.
Simplified Data Management
Row-level security simplifies the process of granting and revoking access – without becoming a blocker to productivity. Using a data security platform that allows you to build row-level access policies in plain language – without requiring SQL expertise – reduces your workload, allowing you to easily delegate data access management to business units.
Increased Flexibility
Row-level security is a more flexible approach to data access control, allowing you to create highly specific access rules tailored to different user roles, locations, and data sensitivity levels. By automating policy enforcement at the row level, you’re able to quickly adapt to changing data access requirements while maintaining control against emerging security threats – and avoiding role explosion. This fosters a more agile and responsive data environment.
Row-Level Security Use Cases
As regulatory pressure and consumer awareness around data security and privacy builds, organizations across industries must do right by not just legislators, but by their customers and employees as well. Here are a few ways they’re using row-level security to make that happen.
Financial Services
We’re all cautious about our personal financial information – it’s why we cut up our old credit cards and shred our bank statements. So it tracks that financial data is subject to stringent compliance standards, such as PCI-DSS.
Implementing row-level security helps meet these standards by ensuring that only authorized users have access to the specific information that is relevant to their work. This protects sensitive financial data, such as bank account numbers, credit card information, and credit history, and minimizes the potential of a security breach or data leak. See how it worked for Swedbank, one of the largest banks in the Nordics.
Healthcare & Life Sciences
Like financial data, health data – whether at the individual level or aggregated in research and clinical trial settings – must be handled with extreme care. This is vital to protecting patients’ privacy, but also because the healthcare industry has the most frequent and expensive data breaches of any industry, with an average cost of $9.7M per incident.
Row-level security helps protect data and meet HIPAA security compliance mandates by enforcing granular protection for specific information, without blocking access to entire tables or data sets. As we saw in our earlier example, this allows different people to perform their jobs efficiently and safely, in order to innovate quickly and improve patient outcomes. Hear from one of Australia’s largest health insurers about doing just that.
Education
From the elementary to the university level, electronic records are now the norm for schools. This makes protecting students’ privacy and achieving the requirements of laws like Family Educational Rights and Privacy Act (FERPA) more important than ever.
Row-level security enforces controls that protect student data, including their grades, attendance records, and eligibility for federal programs such as special education. By tailoring access, RLS facilitates collaboration between educators and administrators, without exposing confidential information. See how AstrumU was able to protect its users’ education data while revolutionizing insights for higher education.
E-commerce
E-commerce businesses store vast amounts of customer information, including contact information, purchase histories, and payment details. For online retailers operating in multiple countries, data localization and sovereignty requirements – including the GDPR – are often difficult to manage, with each jurisdiction having its own standards.
By enabling specific access to relevant data, row-level security allows different departments, such as marketing and customer service, to collaborate efficiently without compromising security or compliance. For instance, you’re able to restrict access to rows based on the user’s location in order to comply with region-specific laws. See how a top streaming service outperformed its goals using flexible, granular controls.
Streamlining Scalable Row-Level Security
Despite its benefits, row-level security is often seen as challenging to set up and maintain, particularly across multiple databases and platforms. Attribute-based access control is the answer to this complexity.
ABAC leverages various attributes, such as geography, time and date, clearance level, and purpose (represented as policy variables) to make dynamic, context-aware access decisions at query time. If a new data set enters the system or user metadata changes, access policies will automatically adjust as necessary – no human intervention required.
ABAC also helps mitigate role explosion, which is a common result of role-based policies that require manual management. Compared to RBAC, ABAC requires 93x fewer policies to manage, which could save $500,000 in operational efficiency.
Protect Your Sensitive Data with Row-level Security
Regardless of your industry, row-level security will help you tap into the value of sensitive data – efficiently, safely, and compliantly. And, implementing RLS across platforms doesn’t need to be a complex or challenging process.
Adopting a data security platform that centralizes policy management and enforcement, and offers dynamic attribute-based access control that can adapt to your business needs, will streamline the process – giving you granular, scalable, and consistent control over your most valuable assets.
Read RBAC vs. ABAC: Future-Proofing Access Control Methods to learn more about the short- and long-term benefits of using ABAC to implement row-level security. Want to see it in action? Talk to a member of our team.