Object storage vs. block storage: Your workload makes the call

Your data doesn't care where it's stored. Your workloads do.

A database that constantly reads and rewrites small pieces of data asks something very different of storage than a data lake holding billions of objects. Choose the wrong architecture, and those differences can surface in performance, scaling, administration, and cost.

So, what separates object storage vs block storage? Object storage stores data as complete objects with metadata and unique identifiers, typically organized into buckets and accessed via APIs.

Block storage divides data into individually addressable blocks and presents them to a host as a disk or volume. Object storage generally fits large-scale unstructured data and API-driven workloads, while block storage suits databases, virtual machines, and workloads that depend on granular updates and consistently low-latency I/O.

Neither is universally better. The useful question is which storage model matches the way your workload behaves. In this guide, I'll use technical research, G2 category data, and G2 user feedback to help you make that call.

Object storage vs. block storage at a glance

The differences become more useful when you connect them to the decisions they affect. This snapshot shows where object vs. block storage diverge, from data access and performance to scaling and cost, before we unpack what those differences mean for your workloads.

What is object storage, and how does it work?

Object storage keeps data as self-contained units called objects. Each one packages three elements:

• Data: The actual content, such as an image, video, backup, or dataset.
• Metadata: Information describing that content, such as its type, owner, or retention rules.
• Unique key: The identifier used to locate and retrieve it.
  Objects are stored in buckets or containers and typically accessed through APIs or SDKs using their keys.

What are the key features of object storage?

I analyzed 80+ tools in G2's object storage solutions category and product-specific G2 user reviews to find capabilities that repeatedly surfaced across different solutions. Seven features showed the strongest category-level patterns:

1. Tiered storage and lifecycle management: G2 reviewers frequently mention hot, cool, and archive-style tiers, along with lifecycle policies that move data as access patterns change.
2. Capacity-planning-free scalability: Across G2 feedback, users commonly describe adding large volumes of data without provisioning conventional storage capacity in advance.
3. Replication and redundancy: Keeping data available through redundancy across infrastructure, zones, or regions is a recurring theme in G2 reviews.
4. API- and SDK-first access: G2 users consistently discuss buckets, object keys, REST APIs, and SDKs as the primary way applications interact with stored data.
5. Fine-grained access control: Permission management also surfaces across G2 feedback through IAM roles, bucket policies, RBAC, and similar controls.
6. Cloud, analytics, and ML integrations: Connections with compute, analytics, data processing, and machine learning services feature prominently in G2 user reviews.
7. Versioning and encryption: G2 reviewers also point to versioning and encryption at rest as recurring ways to protect stored objects.

What is block storage, and how does it work?

Block storage divides data into small, fixed-size pieces called blocks. Each block receives its own address so the system can locate and update it independently. Here’s how the data is handled:

• Blocks: Data is divided into fixed-size chunks.
• Addresses: Each block gets a unique address for independent access.
• Volume: Blocks are presented to a host as a storage volume or device.
• Host access: The volume is typically attached to a single host, where the operating system can create a filesystem on it or an application can work directly with the blocks.

What are the key features of block storage?

I analyzed 45+ products in G2's block storage software category and product-specific G2 user reviews to identify capabilities that repeatedly surfaced across different solutions. Seven features showed the strongest category-level patterns:

• Storage pooling and hyperconverged architecture: G2 reviewers frequently discuss combining disks, hosts, or cloud volumes into shared, software-managed storage.
• Snapshots and point-in-time recovery: Across G2 feedback, capturing volume states and restoring data after failures or unintended changes are recurring requests.
• Elastic volume scaling and live resize: G2 users highlight the ability to expand capacity by increasing volumes, adding disks, or adding hosts as storage needs grow.
• Multiple performance and volume tiers: SSD, NVMe, provisioned-IOPS, throughput-oriented, and other storage configurations feature across G2 reviews for matching performance to workload needs.
• Redundancy and replication policies: G2 feedback frequently highlights replicas, fault-tolerant policies, RAID-style protection, and other approaches for maintaining data copies.
• Encryption and RBAC: Security discussions across G2 reviews include encryption, key management, and role-based permissions.
• Compute and virtualization integration: G2 reviewers repeatedly mention volumes working directly with VMs, cloud instances, and virtualization environments.

Methodology: I reviewed product-specific G2 user feedback across both Object Storage Solutions and Block Storage, analyzing each category separately. I retained features that recurred across multiple products and reviews, excluding isolated product-specific capabilities and generic features not supported by G2 feedback. The seven features for each category represent the strongest recurring patterns from that analysis.

Object storage vs. block storage: 8 key differences that matter

I compared the technical differences between block storage vs object storage with the patterns I found across G2 user reviews. Together, they show where the architectural differences start affecting the decisions teams actually make about their storage.

1. Data architecture: complete objects vs. addressable blocks

The first difference is where responsibility for organizing and managing data sits.

What my G2 analysis shows: Object storage reviews repeatedly surface bucket-and-object management, metadata, and policy controls. Block Storage feedback puts more emphasis on managing storage alongside compute and virtualization.

What this means for you: Object storage carries more management context within the storage layer, while block storage leaves more of that responsibility with the host and application.

2. Access and data modification: API requests vs. granular block updates

The access model matters most when applications need to change data frequently.

What my G2 analysis shows: API- and SDK-based access repeatedly surfaces in G2 Object Storage reviews. Block Storage feedback frequently mentions volumes attached directly to VMs, cloud instances, and database infrastructure.

What this means for you: If several applications or teams need the same data, object storage's network access fits more naturally. If one server needs fast, disk-like access to data that changes constantly, a host-attached block volume is the better match.

3. Performance and latency: throughput at scale vs. low-latency I/O

Performance requirements can quickly narrow the choice, especially when latency and IOPS directly affect application response times.

What my G2 analysis shows: G2 Block Storage reviews repeatedly discuss SSD, NVMe, and provisioned-IOPS tiers for matching performance to workload demands. Object Storage feedback more often connects performance with analytics and large-scale data processing.

What this means for you: If you're evaluating block storage solutions to maintain consistent performance across enterprise peak demand cycles without degradation, test sustained latency and IOPS under the loads you expect to run. For leading object storage solutions for high-performance analytics workloads within your industry, evaluate throughput and retrieval performance against the scale and access patterns of your data.

4. Scalability: horizontal scale vs. volume expansion

Growth affects more than available capacity. It determines how much infrastructure planning teams need as datasets and workloads expand.

What my G2 analysis shows: G2 object storage feedback repeatedly points to growth without advanced capacity provisioning. Block storage reviews highlight the need for live resizing and the addition of volumes, disks, or hosts as requirements increase.

What this means for you: If you're evaluating the best object storage solutions for managing petabyte-scale datasets cost-effectively for your organization, model both storage growth and the access costs that come with it. For block storage, plan for capacity and performance to scale together as infrastructure grows.

5. Metadata: rich object context vs. higher-layer management

Where descriptive context is managed can affect how easily teams classify, find, and govern growing data collections.

What my G2 analysis shows: Metadata, lifecycle policies, and object-level controls repeatedly appear together in G2 object storage feedback. Block Storage reviews focus more on volumes, compute, and infrastructure management.

What this means for you: Object storage gives teams more context to organize and discover large data collections directly at the storage layer. With block storage, that context generally comes from the applications or filesystems managing the data.

6. Cost and pricing: capacity economics vs. performance economics

Storage cost depends on how you use it, not just how much capacity you buy.

What my G2 analysis shows: Egress and retrieval fees are the most recurring pricing concern in G2 object storage reviews. Block Storage feedback more often surfaces pricing and licensing complexity as deployments scale.

What this means for you: When comparing which object storage solutions offer the lowest total cost of ownership at scale, model retrieval, and data movement alongside capacity. If you're evaluating which block storage platforms offer flexible IOPS scaling without unexpected cost increases, compare how both performance and pricing change as workloads grow.

7. Durability and recovery: object redundancy vs. volume recovery

The recovery question is different for stored objects and active application volumes.

What my G2 analysis shows: Object storage reviewers frequently connect these protections with confidence around data availability. Block storage feedback puts more emphasis on dependable restores after workload or infrastructure failures.

What this means for you: For object storage solutions that prevent data loss and ensure durability across regions and implementation support, examine redundancy, versioning, and recovery options alongside deployment support. For secure persistent block storage solutions combined with reliable performance for sensitive production workloads, including disaster recovery requirements in the evaluation, consider how quickly active workloads can be restored.

8. Integration: cloud data ecosystems vs. compute infrastructure

Your existing stack also matters because each storage model connects most naturally with different parts of it.

What my G2 analysis shows: G2 object storage reviews frequently mention connections with analytics, compute, and ML ecosystems. Block storage feedback consistently emphasizes direct integration with VMs, cloud instances, and virtualization environments.

What this means for you: For object storage Solutions providing seamless integration with AWS, Azure, and GCP and implementation support, assess how well storage connects with the services already in your stack. If you're evaluating top object storage solutions platforms for organizations adopting multi-cloud data strategies for enterprise use, factor in portability across providers. On the block storage side, understand how storage fits your cloud virtualization environment and the compute workloads attached to it.

Object storage vs. block storage: Pros and cons G2 reviewers commonly talk about

Earlier, I used G2 reviews to identify what capabilities repeatedly show up across object and block storage products. Here, I looked at the same feedback differently: what did users say got easier after adopting these solutions, and what continued to cause problems? This separates the capabilities themselves from the experiences users associate with them.

*Methodology: For this analysis, I separated capabilities from user outcomes. A capability was treated as a feature, while a pro or con had to reflect a positive outcome or recurring pain point described by G2 users. I retained themes that appeared across multiple products and removed or merged findings that simply repeated the feature list.

How do object storage and block storage compare on G2?

The qualitative differences are clear, but do they translate into a better user experience for either category? I compared G2 satisfaction, adoption, and estimated ROI data for object storage and block storage solutions. The numbers show a close satisfaction race, but a more noticeable difference in time to value.

G2 satisfaction comparison

Across the category-level averages, neither storage model pulls meaningfully ahead.

Both categories reach 90% likelihood to recommend and tie on meets requirements, ease of use, and ease of setup. Block storage leads by just 1–2 percentage points elsewhere, which isn't enough to call either category the stronger overall user experience.

Estimated ROI and adoption

The bigger difference appears in estimated return on investment (ROI).

Object storage solutions show an estimated ROI payback period of 11 months, five months sooner than block storage at 16 months, while adoption is nearly identical at 61% versus 62%.

That gap is worth noting, but not explaining away: the G2 data doesn't establish why object storage reaches estimated ROI sooner. The defensible takeaway is simply that a faster estimated payback is associated with essentially equal adoption.

*Methodology: I used category-level G2 averages rather than individual product highs or lows. Some products have limited response volumes on individual metrics, so category averages give us a more reliable basis for comparing the two categories.

Top object storage and block storage solutions on G2

Once the architecture is clear, product evaluation gets much more focused. Here are the Object Storage and Block Storage solutions from my G2 category research, along with their current G2 ratings and the workloads each is positioned to support.

Top object storage solutions on G2

Top block storage solutions on G2

Akamai Cloud Computing appears in both lists intentionally because G2 categorizes it under both object storage solutions and block storage, showing that a single cloud platform can support both storage models for different workload needs.

Object storage vs. block storage: What should you use?

Your final choice should come down to three questions: How often does the data change? How sensitive is the workload to latency? And how will the data grow? Use those answers to narrow the decision.

There’s also a third scenario to consider. If your teams primarily need to access and share data through familiar files and folders, the decision may extend beyond object and block storage. In that case, explore cloud file storage solutions on G2 to see whether a file-based model better matches how your teams work with data.

Frequently asked questions about object storage vs. block storage

Got more questions? G2 has the answers!

Q1. Why is object storage cheaper than block storage?

Object storage can be cheaper at scale because its economics favor large-capacity storage rather than consistently low-latency, high-IOPS performance. But it isn't always cheaper. Storage tiers, requests, retrieval, and egress can significantly change the total cost.

Q2. Is Amazon S3 object storage or block storage?

Amazon S3 is object storage. It stores data as objects in buckets and accesses them through unique keys and APIs. AWS's block storage service is Amazon Elastic Block Store (EBS), which provides persistent block volumes for EC2 workloads.

Q3. Is SSD block storage?

No. An SSD is a storage medium, while block storage is a storage architecture. SSDs often power block-storage systems because of their low-latency performance, but block storage can use other storage media too.

Q4. What is the difference between object, block, and file storage?

Object storage manages data as metadata-rich objects, block storage divides it into individually addressable blocks, and file storage organizes it into hierarchical files and folders. The best fit depends on how your workload needs to access, modify, and organize its data.

Q5. Is object storage faster than block storage?

Block storage generally provides lower latency for frequent random reads and writes, while object storage can deliver high throughput for large-scale data access. Neither is universally “faster”; performance depends on the workload and access pattern.

Q6. Can databases use object storage?

Yes. Some databases are designed to work with object storage, but traditional transactional databases typically use block storage for active data requiring frequent, low-latency updates. Object storage is also widely used for database backups, exports, and analytics data.

Let the workload make the storage decision

Object and block storage solve different problems, which is why choosing between them gets easier when you stop looking for an overall winner. Start with how your data is accessed and changed, the latency your applications can tolerate, and how you expect capacity to grow. For many environments, the answer may even be both, with each architecture handling the workloads it suits best.

Storage is only one layer of that infrastructure decision. If you're planning how compute, storage, networking, and applications fit together next, explore G2's guide to cloud computing to continue building the bigger picture.

This article was originally published in 2024 by Alyssa Towns. It has been updated with the latest research on object and block storage, G2 user insights, and category data for 2026.