// THREAT DETECTION AND DATA PRIVACY TERM
Storage Limitation
This is a data privacy principle stating that personal data should not be kept for longer than is necessary to fulfill the specific purpose for which it was collected. Once the data is no longer needed, it should be securely deleted or anonymized.
TECHNICAL DEFINITION
Storage Limitation is a fundamental data privacy principle, codified in regulations like GDPR (Article 5(1)(e)), that mandates personal data be retained only for the duration required to achieve the explicit, legitimate purpose for which it was collected and processed. This requires organizations to implement data retention policies, schedules, and secure disposal procedures as a core component of their data governance and lifecycle management strategy.
BACKGROUND
In cryptography, encryption is the process of transforming information in a way that, ideally, only authorized parties can decode. This process converts the original representation of the information, known as plaintext, into an alternative form known as ciphertext. Despite its goal, encryption does not itself prevent interference but denies the intelligible content to a would-be interceptor.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- Data retention principle
- Retention limitation
- Principle of limited retention
- Data storage period limit
- Temporal data minimization
USAGE NOTE
In practice, organizations must define, document, and enforce specific retention periods for different categories of personal data to demonstrate compliance during audits.
DEVELOPERS
Organizations developing technology related to Storage Limitation.
A leading data platform for security and observability, providing solutions to ingest, search, and analyze massive volumes of machine-generated data. Their technology addresses storage limitations through data tiering (hot, warm, cold), compression, and scalable indexing for long-term retention and forensic analysis.
The company behind the Elastic Stack, a popular platform for log management and security analytics. They provide features like Index Lifecycle Management (ILM) to automatically manage data across hot, warm, cold, and frozen storage tiers, optimizing cost and performance for large-scale security data.
A cybersecurity company whose Falcon LogScale technology is designed for high-speed, index-free log management. It enables organizations to ingest and retain vast amounts of security data with significantly lower storage and compute costs compared to traditional SIEM solutions.
A cloud data platform that is increasingly used to build 'Security Data Lakes'. This approach allows security teams to centralize and store petabytes of security data cost-effectively, overcoming the data volume limitations and high costs of traditional security tools for long-term threat hunting and compliance.
A provider of a cloud-native Next-Gen SIEM platform that leverages a big data architecture. Their solution is designed to collect and analyze petabytes of data in real-time, offering unlimited scalability and long-term hot data retention to address storage challenges in modern security operations.
A monitoring and security platform for cloud applications. Their Log Management solution is built to ingest, process, and archive logs at a massive scale, helping security teams manage storage limitations by providing cost-effective retention tiers without sacrificing query performance.
A data security platform that helps organizations manage data sprawl and enforce data minimization principles. By identifying and archiving stale or over-exposed sensitive data, they help reduce the overall storage footprint and attack surface, addressing storage limitations from a data governance perspective.