If you are tasked with protecting sensitive data without breaking the systems that rely on it – think analytics platforms, development environments, or customer-facing applications – Format-Preserving Encryption (FPE) may already be on your radar. Its ability to encrypt data while keeping it structurally intact makes it an appealing choice in modern data architectures. 

However, knowing when FPE is the right solution and how to implement it effectively isn’t always straightforward. This post explores real-world scenarios where FPE excels and outlines key technical considerations for each use case. It’s written for engineers, security architects, and data professionals tasked with securing data while preserving its utility.  

• Note: This post assumes you already have a basic understanding of FPE and how it works. If you’re looking for a breakdown of the underlying cryptography or theory, check out the MasterLabs series or other deep dives. This post focuses on applied usage- where FPE fits and what to consider before deploying it. 

Why Use Format-Preserving Encryption

FPE strikes a balance between data utility and data protection. It allows encrypted data to retain the same format as the original, for example a 10-digit number stays a 10-digit number, and an email still looks like an email. This makes FPE a great fit for systems that can’t tolerate changes in data structure or length, or where realistic but protected data is needed for joins, etc. 

Although, FPE is not always the best choice. In some scenarios, techniques like masking or deterministic tokenization offer a better trade-off between complexity and performance. Below are three common scenarios where FPE does make sense, and what you should think about before implementing it. 

>>> You Might Also Like: MasterLabs – 3 Part Series on Format Preserving Encryption

Format Preserving Encryption Use Cases

1. Internal Access for Dev, QA, and Analytics 

The Problem

Internal teams, such as developers, QA, and data scientists, need access to realistic data to build features, validate functionality, and analyze trends. Exposing raw production data, especially Personally Identifiable Information (PII) in non-production environments poses serious compliance and risk concerns. 

Why FPE Fits 

• Encrypted data retains valid formats – emails still look like emails and phone numbers stay numeric 

• Referential integrity is maintained – joins and filters behave realistically 

• There is no need to modify schemas or rebuild downstream pipelines + UIs to handle encrypted data  

Key Technical Questions 

• Column Selection: Which fields truly require FPE? Prioritize columns based on data sensitivity, regulatory exposure (PII, PCI, HIPAA), and business needs. Some fields may be better suited for masking or tokenization, while others like emails or phone numbers, may need FPE to remain functional in downstream systems 

• Policy Scope: Who gets access to decrypted vs encrypted values? Define fine-grained access based on roles, teams, or job functions. This is easier to manage when the encryption layer integrates tightly with your policy engine, so you can enforce access rules without writing complex code or managing custom logic to make enforcement scalable and auditable 

• Search and joins: Will users need to filter, sort, or join on FPE-encrypted fields? If so, deterministic encryption is essential 

• Performance: FPE introduces some overhead compared to plain text. Performance can vary significantly depending on how encryption is implemented and enforced as not all policy engines are created equal. It’s critical to evaluate performance under realistic query loads, especially with large datasets or high-concurrency workloads 

ALTR’s FPE is deterministic and policy-driven, enabling secure, consistent encryption that supports realistic access patterns without the need for custom enforcement logic or application rewrites. 

>>> You Might Also Like: Secure DevOps Starts with Secure Data Cloning

2. Controlled External Data Sharing (Customers, Partners, Vendors) 

The Problem 

You need to provide controlled access to data that contains sensitive business data – typically to customers, vendors, or partners. This might be through embedded dashboards, reports, or a shared Snowflake reader account. Access must be tightly controlled without degrading the user experience, as data should remain private but useful. 

Why FPE Fits 

• Preserves readability – users can see realistic values, not masked or tokenized placeholders 

• Supports real-time sharing without major changes to existing pipelines, dashboards, or reports 

• Enables differential access- encrypted data for general users, decrypted only for trusted accounts 

Technical Considerations 

• Consistent Encryption: External users expect data consistency, their email, ID, or customer number should look the same across sessions. FPE that is deterministic is essential to ensure this stability 

• Per-Tenant Access Control: When multiple customers share a table, FPE alone isn’t enough. You also need row-level access policies that ensure each external user can only decrypt their own data. This may involve session attributes or secure role-based policies 

• Key Management: Should you encrypt each tenant’s data with a unique key, or enforce access through centralized policies? Separate keys offer stronger isolation but increase operational burden. Policy-based access to a shared key can simplify management while still enforcing strict segmentation. In either case, key rotations need to be managed and upheld 

• Auditability: Do you need logs showing who accessed or decrypted specific records? Integrate logging to trace data access and decryption events 

Tools like Snowflake’s native access controls can help enforce row-level security but pairing them with an FPE engine that includes integrated policy enforcement and detailed audit trails -like ALTR-ensures not just isolation, but also complete visibility into who accessed what, when, and under what conditions. This closes the loop between encryption, access control, and compliance. 

>>> You Might Also: ALTR Key Sharing Meets Snowflake Data Sharing

3. Multi-Tenant Data Isolation in Shared Tables 

The Problem 

You store multiple customers’ data in the same tables – common in SaaS platforms or B2B analytics – and need to ensure tenant isolation for compliance and customer trust. You don’t want to duplicate schema or physically separate each tenant’s data. 

Why FPE Fits 

• Encrypts sensitive fields with tenant-specific context while preserving format 

• Avoids breaking schemas or shared infrastructure 

• Enables secure joins and analytics within tenant boundaries 

Technical Considerations 

• Tenant-aware encryption: FPE should be applied dynamically based on session context or row attributes. That means policies must understand the tenant’s identity and enforce appropriate encryption/decryption at runtime 

• Key scoping and scale: Managing thousands of encryption keys (one per tenant) is complex. Consider using a scalable key hierarchy, key derivation, or centralized policies with per-tenant enforcement logic. 

• Leakage Protection: Strict enforcement is critical – no tenant should decrypt another’s data. This typically requires tight integration between the FPE engine and your data access policy framework 

• Policy Validation: Simulate real-world access scenarios with integration tests. Ensure that your policy engine behaves correctly across edge cases, particularly at scale 

By using ALTR’s policy-driven encryption, you can enforce strict isolation between tenants, protecting sensitive data and maintaining compliance while keeping your infrastructure simple. 

Wrapping up 

Format-Preserving Encryption is a powerful tool for balancing data security with usability, making it an ideal solution for scenarios ranging from customer data protection to tenant isolation in multi-tenant environments. But like any security control, its success depends on thoughtful implementation – clear policy boundaries, smart key management, and realistic performance expectations.

Whether you’re integrating FPE into your existing infrastructure or exploring new ways to secure your data, keeping these technical considerations in mind will set you up for success. As a Field Engineer at ALTR, we work directly with teams to design, test, and deploy data protection strategies that meet real-world needs. Do not hesitate to reach out, we are here to help you get it right from the start.