Top 8 Object Storage Systems for Long Term Data Retention

TL;DR: Object storage keeps huge, unstructured archives durable and immutable for years. Best for on-prem retention: Cloudian HyperStore; best cloud object storage: Amazon S3 (Glacier).

What Are Object Storage Systems for Long-Term Data Retention?

Object storage is the standard for long-term data retention. It replaces traditional tape systems by offering high durability, instant retrieval, and scalability. Instead of sorting files in a tree of folders, object storage places all data into flat pools, saving it alongside custom tags (metadata) and a unique ID number.

Why object storage wins for retention:

• Cost savings: Archival object tiers (such as AWS S3 Glacier or Quantum ActiveScale Cold Storage) reduce storage costs by up to 80% compared to standard hot storage.
• Scalability: It scales seamlessly from terabytes to exabytes without slowing down.
• Immutability: Features like “WORM” (Write Once, Read Many) lock data to prevent deletion or ransomware changes for mandated retention periods.
• Erasure coding: Instead of making full file copies, the system breaks data into mathematical fragments and scatters them across nodes. This guarantees data stays intact even if multiple drives fail.

In this article:

Quick Comparison: Object Storage Systems for Long-Term Retention

The table below summarizes the key differences between the systems covered in this article. We explore each of them in more detail in the sections that follow.

Why Long-Term Data Retention Requires a Dedicated Storage Strategy 

Growing Data Volumes

The exponential growth of data in modern enterprises is driven by digital transformation, IoT, analytics, and regulatory requirements. As organizations generate and collect more information, traditional storage systems become difficult and expensive to scale. File and block storage architectures often hit practical or cost limits when dealing with petabytes of unstructured data, making them unsuitable for long-term retention at scale.

Object storage addresses these challenges by providing a flat namespace and virtually unlimited scalability. This enables organizations to accommodate ever-growing data volumes without the need to constantly rearchitect or migrate storage systems. The efficiency of object storage also reduces administrative overhead, allowing IT teams to focus on managing policies and access rather than infrastructure limitations.

Ransomware and Data Tampering Risks

Ransomware attacks and data tampering incidents are increasingly common and can have devastating consequences, particularly for long-term archives. Traditional storage systems may lack features that protect against unauthorized modification or deletion, leaving organizations vulnerable to loss or corruption of critical data. The inability to ensure data immutability in file or block storage further increases these risks.

Object storage systems often include built-in immutability features such as write-once-read-many (WORM) capabilities and time-locked retention policies. These controls prevent data from being altered or deleted for a specified period, even by administrators. As a result, object storage provides a robust defense against ransomware and insider threats, ensuring that archived data remains intact and trustworthy over the long term.

Related content: Learn more about how object storage protects you from ransomware.

Regulatory Retention Requirements

Many industries are subject to strict regulations that dictate how long data must be retained and how it must be protected. Healthcare, finance, legal, and government sectors often require data to be stored for years, sometimes decades, with guarantees of integrity and accessibility. Non-compliance can lead to severe penalties, legal action, or reputational damage, making regulatory adherence a top priority.

Object storage is well-suited for regulatory compliance due to its support for retention policies, audit trails, and immutable storage. Administrators can define rules to enforce data retention periods, prevent premature deletion, and provide evidence of data integrity. The ability to tag objects with metadata also simplifies classification and retrieval for audits or legal holds, reducing the complexity and cost of meeting regulatory obligations.

Why Object Storage Wins for Retention 

Cost Savings

Object storage is designed to optimize costs for long-term data retention. By decoupling storage capacity from performance, organizations can use commodity hardware and scale out as needed. This reduces upfront investment and ongoing maintenance expenses compared to traditional storage solutions that often require proprietary hardware or complex architectures. Cloud-based object storage options further lower costs by shifting to an operational expenditure model, allowing organizations to pay only for the storage they use.

Additionally, object storage systems often feature built-in data reduction technologies such as deduplication and compression. These features minimize the physical storage footprint, further lowering the total cost of ownership. The ability to automate data tiering and move infrequently accessed data to lower-cost storage classes also contributes to significant savings over the data lifecycle, making object storage a financially attractive solution for long-term retention.

Scalability

One of the main advantages of object storage is its ability to scale seamlessly to accommodate growing data sets. Traditional file and block storage systems are often constrained by architecture or performance bottlenecks, making expansion difficult and costly. Object storage, in contrast, uses a flat namespace and distributed architecture, which enables organizations to add capacity without disrupting operations or restructuring existing data.

This scalability is critical for enterprises dealing with unpredictable or exponential data growth. Object storage systems can be deployed on-premises, in the cloud, or in hybrid configurations, offering flexibility to match business needs. As a result, organizations can confidently plan for future growth, knowing that their storage infrastructure will not become a limiting factor for long-term data retention.

Immutability

Immutability is a key feature of object storage that protects data from unauthorized modifications or deletion. With features like WORM and retention policies, organizations can ensure that critical data remains unaltered for the required retention period. This is particularly important for compliance with regulations such as SEC 17a-4, HIPAA, or GDPR, where data integrity and preservation are mandated by law.

In addition to compliance, immutability serves as a defense against ransomware and insider threats. By locking data against changes, object storage systems prevent attackers from encrypting, deleting, or altering archived files. This ensures that backup and archival data remain a reliable source for recovery and investigation, providing peace of mind for organizations facing evolving security threats.

Erasure Coding

Erasure coding is a data protection mechanism commonly used in object storage systems. It breaks data into fragments, encodes them with redundant pieces, and distributes them across multiple disks or nodes. This approach provides high durability and fault tolerance while using less storage overhead than traditional replication. If a disk or node fails, the system can reconstruct the lost data from the remaining fragments, ensuring continuous availability.

The efficiency of erasure coding makes it especially valuable for long-term retention, where data durability and storage costs are top concerns. Unlike simple replication, which multiplies storage requirements, erasure coding achieves the same or higher levels of protection with less capacity. This allows organizations to store large volumes of data securely and cost-effectively, without sacrificing performance or resilience.

Object Storage vs. File Storage vs. Block Storage vs. Tape Storage: Which Is Best for Long-Term Data Retention?

Organizations can retain data using file storage, block storage, tape, or object storage, but each architecture is designed for different workloads. File and block storage prioritize active applications and frequent access, while tape focuses on low-cost offline archives. Object storage combines massive scalability, high durability, rich metadata, and policy-based data protection, making it the preferred architecture for long-term retention of large volumes of unstructured data.

The following table summarizes the differences between these storage options.

Notable Object Storage Systems for Long-Term Retention

How we selected these systems: We shortlisted object storage systems based on data durability, immutability and retention controls (WORM/Object Lock), scalability, and lifecycle management for storing data over the long term.

On-Premises and Software-Defined Object Storage Platforms

1. Cloudian HyperStore

Best for: On-prem and hybrid S3 storage with data sovereignty

Strengths: S3 Object Lock, geo-distribution, multi-tenant, per-bucket configuration, exabyte scale

Things to consider: Monitoring UI can take extra steps to navigate

Cloudian HyperStore is software-defined object storage that runs on industry-standard servers or Cloudian appliances, on-premises or across hybrid clouds. It presents distributed sites as a single flat S3 namespace managed through one console and one set of credentials.

The platform uses a shared-nothing, peer-to-peer architecture with no central metadata server or head node. Every node serves I/O, so capacity and throughput scale together as nodes are added, and the system stores unstructured data at exabyte scale with non-disruptive expansion at one site or across many.

Key features include:

• S3 API compatibility: Full support for AWS S3 features and operations using the AWS S3 SDK, for data management and interoperability across hybrid and multi-cloud environments.
• S3 Object Lock (WORM): Stores objects in an immutable state that cannot be altered or deleted by any user, including the root administrator, until the retention period expires; supports Compatible and Certified retention modes plus Legal Hold, and has been assessed against SEC 17a-4(f), FINRA 4511, and CFTC 1.31.
• Erasure coding and replication: ISA-L erasure coding distributes data fragments across nodes, racks, or data centers, and the protection scheme is set per bucket; the system can withstand drive, node, rack, and full-site failure.
• Cyberstorage ransomware defense: Overwrite-encryption protection blocks unauthorized object overwrites at the system or bucket level and alerts administrators, while audit logging records unauthorized deletion attempts.
• Encryption and key management: AES-256 at rest through SSE, SSE-C, SSE-KMS, and SSE-KMIP with external KMIP systems, TLS 1.2/1.3 in transit, and a FIPS 140-3 Level 1 validated cryptographic module.
• Multi-site placement and tiering: Per-bucket placement, synchronous or asynchronous replication, and lifecycle policies, with the option to tier data to public cloud as it ages.
• Secure multi-tenancy: Per-tenant users, IAM policies, role-based access controls, and QoS rate limits that isolate tenants and prevent noisy-neighbor effects.

Limitations (as reported by users on G2):

• Monitoring and reporting views: Some users find the monitoring and reporting interface could be more intuitive and say it occasionally takes extra steps to locate details.
• Advanced configuration: A few reviewers note that advanced configuration can benefit from additional documentation or hands-on guidance.
• Concurrent access: One reviewer felt performance could be stronger when a large number of users access data at the same time.

2. NetApp StorageGRID

Best for: Long-term retention and backup across hybrid cloud

Strengths: ILM policy engine, S3 Object Lock, erasure coding

Things to consider: High VM RAM/CPU and raw-capacity overhead

NetApp StorageGRID is software-defined object storage that manages globally distributed data under a single namespace with native S3 support. It can run on hardware appliances, virtual machines, or Docker containers, or a combination across physical and virtual environments.

Its metadata-driven information lifecycle management engine places content on the right storage tier at the right time and enforces retention over long periods, which makes it a common choice for backup and archive workloads.

Key features include:

• Information lifecycle management (ILM): A dynamic policy engine automates data placement and retention across tiers based on rules, supporting privacy, security, regulatory compliance, and data management needs.
• S3 Object Lock immutability: Extends immutability for long-term retention, helping prevent deletion, modification, or encryption, with compliance and governance modes and the ability to restore to a known-good state.
• Data durability: Replication and layered erasure coding protect data across sites, and at-rest and in-flight data verification maintains integrity for long-term retention.
• Unified namespace and grid federation: Manage multiple StorageGRID systems as a single namespace to operate at global scale without re-architecting.
• Flexible deployment: Hardware appliances such as the SGF6212 and SG6260, virtual machines, or Docker containers on bare-metal servers.
• Cloud tiering and integration: Policy-based ILM can store objects to public clouds including AWS and Azure, and StorageGRID integrates with NetApp ONTAP FabricPool to tier cold data off primary storage.
• Security and governance: Encryption, access controls, and multi-admin verification strengthen administrative security and support data governance standards.

Limitations (as reported by users on G2):

• Resource requirements: Reviewers report it can require virtual machines with high RAM and CPU, and that erasure coding adds notable raw-to-usable capacity overhead.
• Cost: Several users describe the overall cost of the solution as high.
• Front-line support: Some users find it difficult to reach advanced support tiers and feel front-line support could be improved.
• Integration and network dependence: One reviewer noted integration can be challenging and that performance is affected by slow network connections.

3. Scality RING

Best for: Petabyte-to-exabyte on-prem archives and backup

Strengths: 14 nines durability, S3 Object Lock, low TCO

Things to consider: Encryption and full S3 parity have gaps

Scality RING is scale-out file and object storage software that runs on industry-standard x86 servers. It scales across capacity, performance, sites, and clouds under a single S3 namespace and supports both object access through S3 and file access through NFS and SMB.

The software is positioned for large, long-term repositories such as active and compliance archives, using a distributed, single-system design that aims to keep data available during failures, upgrades, and expansions.

Key features include:

• Multidimensional scale-out: Scales in capacity, performance, buckets, servers, and sites without fixed capacity or performance limits, from one workload to many.
• Data durability: Erasure coding, replication, and self-healing provide up to 14 nines of data durability, with multi-geo options that distribute data across availability zones.
• S3 Object Lock immutability: Renders data immutable once written, with configurable retention policies and a compliance mode.
• CORE5 cyber resilience: Five levels of protection spanning the API to the architecture, aimed at ransomware and other threats.
• Security and access: AWS-compatible IAM and MFA for multi-tenancy, 256-bit encryption at rest, and HTTPS connections.
• Hybrid-cloud S3 namespace: Full S3 API support to move data across on-premises and cloud from a single system.
• Hardware freedom and TCO: Software-defined, pay-as-you-grow deployment on standard servers, with vendor-cited TCO savings of 50 to 70 percent versus alternatives.

Limitations (as reported by users on PeerSpot):

• Encryption and data security: Users report encryption capabilities are dated and note gaps for customers with strict confidentiality requirements.
• S3 compatibility gaps: Some users report that certain S3 functions, such as checksums expected by some backup tools, are not fully supported.
• Setup and updates: Initial setup can be complex, and frequent updates and patches can affect stability and add to operational cost.
• Resource sharing: Sharing capacity across S3, NFS, and SMB services can require dedicated allocation per service, which some users find inefficient.

4. MinIO AIStor

Best for: S3-compatible object storage for AI and analytics

Strengths: Object Lock, versioning, lifecycle, 11 nines durability

Things to consider: Docs gaps; monitoring and upgrades can be tricky

MinIO AIStor is software-defined, S3-compatible object storage that scales from petabytes to exabytes in a single namespace and can be deployed at the edge, core, or cloud. It provides object immutability, versioning, lifecycle management, replication, and encryption within one system.

Its data-management capabilities are designed to consolidate versioning, retention, inventory, and compression under shared IAM policies, audit logs, and encryption, rather than assembling those functions from separate services.

Key features include:

• S3 compatibility: Native S3 API for objects, with support for tables through Apache Iceberg and files through SFTP.
• Object immutability and versioning: Immutable object versioning protects against accidental deletion and overwrites, and versioning can be set at the bucket level or selectively by prefix.
• Lifecycle management: Declarative policies expire objects or transition them to cold storage tiers based on object age, tags, prefixes, or version state.
• Data durability: Erasure coding and bit-rot protection are designed for 11 nines of data durability.
• Encryption and key management: Encryption paired with an integrated key management server, plus anti-ransomware and compliance controls.
• Inventory and compression: Scheduled inventory jobs catalog namespace metadata without expensive listing calls, and inline MinLZ compression reduces the storage footprint during writes.
• Compliance support: Immutable versioning provides tamper-proof audit trails that support SOC 2, HIPAA, FINRA, and SEC 17a-4 requirements.

Limitations (as reported by users on G2):

• Documentation and expertise: Users report that administration can be difficult at times due to gaps in documentation and the engineering expertise required.
• Operational stability: Some users report occasional stability issues in the availability of APIs and services.
• Upgrades and compatibility: A few users find upgrades and key rotations without data loss tricky, and cite backward-incompatible releases causing issues.
• Portal limitations: One reviewer noted the UI or portal has limitations in some environments.

Cloud Object Storage Services

5. Amazon S3 (Amazon Simple Storage Service)

Best for: Cloud object storage and archival at any scale

Strengths: 11 nines durability, Glacier tiers, Object Lock

Things to consider: Pricing and IAM policies can be complex

Amazon S3 is the AWS object storage service that stores data from bytes to exabytes, scaling elastically with pay-per-use pricing. It offers multiple storage classes with automated lifecycle management and is encrypted by default with access controls and auditing.

For long-term retention, the S3 Glacier storage classes provide low-cost archival with a range of retrieval options, from millisecond access to multi-hour bulk retrieval, so archives can be matched to how quickly the data needs to come back.

Key features include:

• Durability and availability: Designed for 11 nines of data durability and 99.99 percent availability, with data stored redundantly across multiple Availability Zones.
• Glacier archive storage classes: Glacier Instant Retrieval for millisecond access, Glacier Flexible Retrieval for minutes-to-bulk retrieval in 5 to 12 hours, and Glacier Deep Archive with retrieval within 12 hours for long-lived archives.
• Object Lock (WORM): Enables write-once-read-many storage to help meet retention and compliance requirements.
• Storage classes and lifecycle management: Automated lifecycle policies and S3 Intelligent-Tiering move data between classes to manage cost.
• Security and encryption: Encrypted by default, with three forms of encryption on the Glacier classes and CloudTrail logging of API activity for auditing.
• Compliance certifications: Glacier classes support SEC 17a-4, PCI-DSS, HIPAA/HITECH, FedRAMP, GDPR, and FISMA.
• Analytics and AI foundation: Used as the basis for data lakes, with S3 Tables adding native Apache Iceberg support and S3 Vectors adding vector storage and query.

Limitations (as reported by users on G2):

• Pricing complexity: Users find pricing hard to predict, with data egress, request, and retrieval charges that can add up at scale.
• Permissions management: Managing IAM policies and permissions can be complex and error-prone, especially for newer users.
• Console learning curve: The console can be difficult to navigate for users who are not already familiar with AWS.
• Large-bucket management: Working with buckets that hold millions of objects can be cumbersome without well-defined lifecycle policies.

6. Microsoft Azure Blob Storage

Best for: Cloud object storage for data lakes and archives

Strengths: Immutable WORM, access tiers, lifecycle management

Things to consider: Egress costs and console usability

Azure Blob Storage is Microsoft’s cloud object storage for unstructured data such as text and binary files. It offers multiple access tiers with automated lifecycle management, integrates with other Azure services, and supports analytics through Azure Data Lake Storage.

It is built for scenarios ranging from serving images and documents to storing backups and archiving data, and it can replace tape archives with tiered storage that shifts data to lower-cost classes over time.

Key features include:

• Storage tiers: Premium SSD-based, Hot, Cool, Cold, and Archive tiers based on how often data is accessed, with reserved capacity for cost savings.
• Lifecycle management and WORM: End-to-end lifecycle management, policy-based access control, and immutable write-once-read-many storage.
• Durability and replication: Sixteen-nines designed durability with geo-replication.
• Security: Authentication with Microsoft Entra ID, role-based access control, encryption at rest, and advanced threat protection.
• Data lake support: Azure Data Lake Storage extends Blob Storage with a file namespace and multi-protocol access optimized for analytics workloads.
• Developer support: Supports frameworks including Java, .NET, Python, and Node.js, with an SSD-based premium tier for low-latency scenarios.
• Compliance: More than 100 compliance certifications, including many specific to regions and countries.

Limitations (as reported by users on G2):

• Data transfer costs: Users note that data transfer and egress costs can rise sharply and that pricing can be hard to figure out.
• Onboarding: Some users find it not easy to use out of the box, with documentation that can be hard to find and follow.
• Portal views: One reviewer noted limited ability to customize table and metadata views within the portal.

7. Google Cloud Storage

Best for: Cloud object storage with tiered archival classes

Strengths: Bucket Lock retention, lifecycle, Autoclass

Things to consider: Permission setup and billing can be complex

Google Cloud Storage is a managed object storage service for unstructured data, with storage classes spanning frequent to archival access. All classes have millisecond latency and are reached through a single API, and the service offers policy-based lifecycle management plus integration with Google Cloud analytics and machine learning tools.

It provides a range of retention and data-protection controls that suit long-term storage, along with continental-scale replication options for availability across regions.

Key features include:

• Storage classes: Standard, Nearline (30-day), Coldline (90-day), and Archive (365-day) classes, all with millisecond latency through one API.
• Automatic transitions: Object Lifecycle Management and Autoclass move objects between classes based on age or last access time.
• Retention and immutability: Retention policies, retention policy locks, Bucket Lock, object holds, object versioning, and soft delete.
• Security and access: IAM for object- and bucket-level permissions, uniform bucket-level access, and customer-managed or customer-supplied encryption keys.
• Replication: Dual-region and multi-region buckets, with a continental-scale bucket spanning nine regions and turbo replication offering a 15-minute recovery point objective.
• Management at scale: Storage Intelligence with Insights Datasets, Batch Operations, and Bucket Relocation for managing large estates.
• Analytics and ML integration: Integrates with BigQuery, Managed Service for Apache Spark, and Google’s AI tools, and Cloud Storage FUSE allows filesystem-style access.

Limitations (as reported by users on G2):

• Permission setup: Configuring bucket, directory, and file permissions can be difficult, and the access-control options are extensive for new users.
• Billing clarity: Users find the billing dashboard overwhelming and some charges, such as egress, hard to identify.
• Pricing and free tier: Some users find pricing high for smaller needs and the free tier limited.
• Interface navigation: The breadth of the platform can make it difficult to navigate initially.

8. Wasabi Hot Cloud Storage

Best for: Low-cost single-tier cloud backups and archives

Strengths: No egress/API fees, immutability, S3 compatible

Things to consider: One tier only; console and permissions setup

Wasabi Hot Cloud Storage is S3-compatible cloud object storage that uses a single storage tier and does not charge for egress or API requests. It targets backups, archives, and hybrid-cloud workloads, with reserved-capacity pricing for longer commitments.

Because there are no separate archive or warm tiers, all data is stored in one hot tier with low-latency access, which the vendor positions as a target for active archives, offsite backups, and cloud tiering.

Key features include:

• Single-tier storage: One hot tier for all data removes tier management, with reserved capacity storage for lower long-term cost.
• Pricing model: No egress or API request fees, with vendor-cited costs up to 80 percent below the hyperscalers.
• Immutability and protection: Object-level immutability through Object Lock, virtual air-gapping through Covert Copy technology, and Multi-User Authorization.
• Security: SOC-2 and ISO 27001-certified data centers, server-side encryption, and MFA, IAM, and SSO controls.
• Durability and availability: 11 nines of durability and 99.9 percent system availability.
• S3 compatibility: An S3-compatible API for integration with existing tools, with up to 100 Gbps direct connect speeds.
• Deployment option: Wasabi with Dell ObjectScale delivers the capabilities of on-premises Dell ObjectScale as a service.

Limitations (as reported by users on G2):

• Permission configuration: Setting bucket permissions relies on a technical policy editor that some users find obscure.
• Console usability: Several users find the management portal not the most intuitive and note that documentation can be hard to read.
• Single-tier tradeoffs and retention: The single-tier model suits many use cases but not all, and users note a minimum storage duration and limited handling of frequently changing files.

Conclusion

Object storage provides a scalable, cost-effective, and highly durable architecture essential for managing long-term data retention. By leveraging features like immutability and erasure coding, organizations can safeguard massive datasets against ransomware and ensure regulatory compliance. Whether deployed on-premises or in the cloud, these systems simplify data management and guarantee accessibility for years to come.