Guide to Data Archiving

Data archiving is the process of storing inactive or historical data for long-term retention. It’s designed to help you keep what matters without weighing down your active systems.

Unlike live data, archived data isn’t accessed frequently. It’s pulled when needed—for audits, compliance checks, or reference purposes—and stored in a way that balances cost, accessibility, and security. Archiving is partly about offloading, but it’s also about organizing data in a way that supports business goals. Think performance gains, easier storage management, legal readiness, and institutional memory.

Common use cases for data archiving solutions include:

• Preserving historical data for audits or legal obligations
• Reducing storage strain and keeping active systems performant
• Supporting compliance with long-term retention policies
• Maintaining access to institutional knowledge across teams

By integrating archiving into your broader data lifecycle strategy, you can manage growth more efficiently and reduce the risk of costly overages or compliance gaps. The result? A more agile, organized, and future-ready system.

Data archiving and data backup are often lumped together, but they address different problems, and confusing one for the other can lead to gaps in both protection and performance.

Backup is built for short-term recovery. It creates a copy of your current system so you can quickly restore data in the event of a failure, outage, or accidental deletion. These copies are designed to be temporary and optimized for speed rather than longevity.

Archiving, on the other hand, is meant for long-term retention. Archived data is typically inactive and doesn't need to be restored quickly; however, it must remain searchable, secure, and accessible over time.

Key differences include:

• Purpose: Backup is about recovery; archiving is about retention
• Lifespan: Backups are short-lived; archives can last for years
• Structure: Backups capture everything; archives store selected records
• Access patterns: Backups are rarely touched unless something goes wrong; archives are queried for audits, reporting, or legal need.

For example, Salesforce Backup & Recover is built to restore lost data fast, while archiving strategies help you store completed records like closed opportunities or expired contracts without cluttering your live system.

The smartest approach? Use both.

A well-executed strategy reduces cost, preserves insight, and helps you stay ready for whatever comes next. Let’s dive into the details.

When inactive data piles up in your active system, it slows everything down. Archiving moves that data to lower-cost storage, reducing query load, speeding up searches, and keeping core processes running smoothly.

By separating what you need now from what you might need later, teams can work faster—and systems stay leaner.

Storage limits can sneak up fast, especially in CRM or ERP systems. Archiving lets you offload rarely-used data while keeping it accessible, which helps you avoid costly overages and slowdowns.

It also helps simplify reports by removing historical data that clutters dashboards and slows analytics tools.

Certain data can’t just be deleted—it needs to be retained, protected, and retrievable for audits, legal requests, or regulatory compliance.

Archiving helps you meet standards outlined in policies like GDPR and CCPA, while maintaining access to records even if they’re years old.

Many archiving solutions include support for legal holds, defensible deletion, and defined retention timelines, which are key components of any compliance-driven archiving strategy.

There's long-term value in old data. Archiving enables you to preserve customer interactions, project records, and business decisions, providing your teams with historical context when forecasting or reviewing past performance.

Instead of starting from scratch, you can look back, spot trends, and build from a complete picture of what came before.

Not all data needs to be live, but not all of it should be deleted. A smart archiving plan starts by identifying which records are no longer part of daily operations but still carry legal, historical, or strategic value.

Common examples include:

• Closed cases and completed opportunities
• Inactive contacts and users
• Expired contracts and old transactions
• System logs and audit trails
• Historical marketing campaign data
• Outdated product catalogs or price books

Candidates for archiving include structured data, like CRM records, database tables, and transactional entries, and unstructured data, such as email attachments, documents, and notes. If you’re using Salesforce, typical candidates for archiving include:

• Closed support cases older than a year
• Historical opportunities no longer tied to current accounts
• Inactive leads, contacts, or users with no recent activity

Archiving this type of data helps keep systems responsive while preserving the information your teams or auditors might need in the future.

Archiving data can deliver long-term benefits, but without a clear plan, it can just as easily create complexity, confusion, or compliance risk. Here are a few common pitfalls and how to avoid them:

As archived data grows, so does the potential for disorganization. Without a clear structure, it’s easy to lose track of what’s stored, why it’s stored, or whether it should have been deleted.

The fix: use metadata, tagging, and dashboards to keep archives searchable and segmented by type, age, or purpose. If you're archiving from legacy systems, plan your migration carefully to modern, flexible storage that supports indexing and automation.

Regulations like GDPR and CCPA require more than just keeping data. You need to prove how it’s handled. That means retaining it securely while also being able to delete or produce it when necessary.

Make sure your archiving setup supports audit trails, access tracking, and defensible deletion. Tools designed with data privacy in mind help ensure archived records are protected while still being accessible when needed.

You can approach data archiving with clarity and control by following these data archiving best practices.

Define what data needs to be archived, retained, or deleted based on business requirements, legal obligations, and compliance timelines. Group records by type, sensitivity, or how long they must be kept.

Set clear rules about when data should move to archives, how long it stays there, and when it should be purged. Establishing these guidelines ensures consistency across teams and aligns your organization with regulatory expectations.

Manual archiving can be time-consuming and prone to error. Use automation to flag, move, and track data based on predefined triggers or retention timelines. That means fewer mistakes and less time spent on repetitive tasks.

Security matters, too. When testing automation workflows, ensure that you're not exposing sensitive records—tools like data masking can help protect them during development and QA environments.

Archived data should never feel lost. Utilize indexing, tagging, and metadata to facilitate easy location when needed. Regularly test your retrieval process, especially for high-risk data types or industries with regulatory requirements.

Align deletion schedules with retention policies and ensure that documentation is kept up to date. If you're ever audited, you'll need to demonstrate not only what you stored but also how and why.

Track key metrics: improved system performance, reduced storage usage, successful automation runs, and archive access trends.

Compliance readiness is another benchmark—can your teams quickly find and produce data when asked? Are retention policies being followed across systems?

Finally, evaluate the return: the cost of your archiving tools compared to the value they deliver in storage savings, reduced risk, and improved operational efficiency.

Not all archives are built the same. Depending on the type of data you manage and your business requirements, different approaches may work better. Here are four common types of data archiving solutions to consider:

Used for storing structured data from systems such as CRMs, ERPs, or HR platforms, this method moves inactive records, including closed opportunities or outdated employee profiles, into long-term storage.

It improves performance by separating live data from historical data. It is ideal for archiving transactional records that are no longer needed on a day-to-day basis but still need to be preserved.

Designed for unstructured data, this type of archiving stores documents, spreadsheets, email threads, and attachments. It helps reduce strain on primary storage systems and supports audits, e-discovery, and legal hold requests.

Most solutions offer indexing and search capabilities to help teams retrieve what they need, even years later.

Cloud-based archiving platforms, such as AWS Glacier, Azure Archive, or Google Cloud Storage, offer scalable, cost-effective options with remote access and automated lifecycle tools.

On-prem solutions may provide more control and meet data residency or security requirements but often require more hands-on maintenance. Many organizations use cloud storage to reduce infrastructure costs while retaining long-term flexibility.

Hybrid solutions combine cloud and on-premises storage to strike a balance between cost, performance, and compliance.

They're especially useful during transitions from legacy infrastructure or when regulatory requirements differ across regions or departments. These setups allow archived data to remain accessible through core business systems, even if physically stored off-site.

Choosing the correct data archiving tool is as important as archiving itself and requires careful consideration of several key factors.

Start with the essentials:

• Automation to reduce manual effort
• Indexing and search capabilities to keep archived data accessible
• Security features like encryption, access controls, and audit trails
• Integration support to work smoothly with your existing platforms
• Scalability to handle growing volumes of structured and unstructured data

Solutions like Salesforce Archive are designed to manage large datasets while aligning with automation and compliance goals.

Before you choose a solution, make sure you understand:

• Does it scale with your projected data growth?
• Can it integrate with systems like Salesforce?
• How does it handle retrieval, restoration, and access logging?
• What options exist for configuring retention policies and defensible deletion?

These questions help surface whether a solution is built to handle both your operational and regulatory requirements—now and in the future.

Start with the data that creates the most impact: large volumes, regulated records, or high-cost storage areas. Run pilot workflows in a test or staging environment to fine-tune before going live.

Document roles, responsibilities, and user access policies early. A clear plan upfront makes for a smoother rollout and reduces friction as your archiving strategy scales.

Salesforce offers several options to help you manage large volumes of historical data without compromising system performance or compliance posture.

The most comprehensive Salesforce archiving solution with our native data archiving solution, Salesforce Archive. With Archive, you can create automatic archiving policies, seamlessly view archiving processes from end to end, and quickly retrieve or search archived data.

For long-term storage of structured, read-only records, features like Salesforce Big Object provide a scalable way to archive data within the platform. You can automate archiving workflows using Salesforce Flow or custom Apex jobs, making it easier to stay consistent while reducing manual lift.

Third-party options available on the Salesforce AppExchange offer additional flexibility, whether you’re integrating with external cloud storage providers or adding advanced features like policy-based automation or tiered storage.

See just how Salesforce data archiving tools are built to support your performance, compliance, and retention goals as your organization grows.