11 Enterprises are generating more unstructured data across backup, AI, analytics, media, healthcare, research and cloud-native applications. As those datasets grow into petabytes, the infrastructure underneath them has to scale without creating new operational or economic constraints. Public cloud object storage is one option, but it is not the right deployment model for every workload. Data sovereignty requirements, security policies, performance needs, predictable cost models and the need for direct infrastructure control are keeping on-premises storage central to many enterprise architectures. That has increased demand for modern, S3-compatible object storage that can run inside an organization’s own data center or private cloud. So, what is the best on-prem object storage for enterprise environments? There is no single feature that determines the answer. The strongest platforms combine scale, durability, cyber resilience, S3 compatibility, operational simplicity and deployment flexibility. Scality is designed around these requirements, with different platforms addressing large-scale enterprise infrastructure, AI and backup use cases. What is on-prem object storage? On-prem object storage stores data as objects within infrastructure controlled by the organization rather than placing the primary storage environment in a public cloud. Each object typically includes the data itself, metadata and a unique identifier. Applications interact with the storage through APIs, most commonly the Amazon S3 API. This architecture makes object storage particularly well suited to large volumes of unstructured data, including: Backup and recovery data AI training and inference datasets Images, video and media libraries Medical imaging Research and genomics data Application data Log and analytics data Long-term archives Data lakes Modern on-prem object storage brings the scale-out model associated with cloud storage into enterprise-controlled infrastructure. Capacity can grow by adding resources rather than repeatedly replacing a traditional storage system with a larger one. Organizations also retain direct control over where data resides, how infrastructure is secured and how storage resources are operated. Why enterprises choose on-prem object storage The growth of public cloud storage has not eliminated the case for enterprise-owned storage infrastructure. For many workloads, on-prem object storage provides advantages that become increasingly important as datasets grow. Data control and sovereignty Keeping data on premises gives organizations greater control over its physical location and the infrastructure responsible for storing it. This can be important for organizations operating under data residency, sovereignty, governance or industry-specific requirements. It can also simplify architectural decisions when sensitive datasets cannot be freely moved between jurisdictions or third-party cloud environments. S3-compatible object storage allows organizations to maintain this control while still giving applications access to a widely adopted object storage interface. Predictable storage economics Public cloud storage can work well when infrastructure flexibility outweighs long-term capacity costs. At sustained petabyte scale, however, organizations also have to account for retrieval, API, network and data movement costs in addition to raw storage capacity. On-prem object storage moves the economic model toward infrastructure that the organization owns or directly controls. This can make costs more predictable for large datasets that are retained for years or accessed frequently, particularly when workloads would otherwise generate substantial cloud data movement. Data locality Some workloads benefit from keeping compute and storage close together. AI is a clear example. Training, inference and data preparation pipelines can involve very large datasets, and repeatedly moving those datasets between an enterprise environment and a public cloud can introduce additional latency, network demand and cost. The same principle applies to backup, analytics, media processing and other data-intensive applications. Infrastructure flexibility Software-defined object storage can separate the storage software from a proprietary appliance lifecycle. This gives enterprises more flexibility to select infrastructure appropriate to capacity, performance and budget requirements while evolving hardware over time. For environments expected to operate for many years, that flexibility can be important to overall storage economics. What makes the best on-prem object storage? Evaluating enterprise object storage requires looking beyond raw capacity. A platform that can store several petabytes still needs to protect that data, remain available through failures and upgrades, integrate with applications and remain manageable as the environment grows. Several capabilities should be part of any evaluation. 1. Scale-out architecture Scalability is one of the fundamental reasons enterprises adopt object storage. A strong platform should allow organizations to add storage resources without redesigning the environment or migrating existing data every time additional capacity is required. The evaluation should also go beyond capacity. Modern workloads can change in several dimensions at once, including: Capacity Throughput Object count Users and tenants Geographic locations Applications and workloads An architecture designed for multidimensional growth gives organizations more flexibility as infrastructure requirements change. Scality RING, for example, uses a distributed scale-out architecture designed for very large enterprise and service-provider environments. Scality’s MultiScale Architecture is designed to allow infrastructure to scale independently across critical dimensions rather than treating storage growth solely as a capacity problem. 2. S3 compatibility Amazon S3 has become a common API for object-based applications and data protection platforms. For on-prem environments, S3 compatibility allows applications built around cloud object storage models to access enterprise-controlled infrastructure using familiar APIs. This can support applications including backup platforms, analytics tools, AI pipelines and internally developed software. S3 compatibility can also reduce dependence on proprietary storage interfaces. When evaluating platforms, organizations should consider the depth of S3 API support required by their applications rather than treating basic S3 compatibility as a simple checkbox. 3. Cyber resilience and immutability Storage infrastructure has become part of the enterprise cybersecurity architecture because ransomware attackers increasingly target backup and recovery data. S3 Object Lock can make stored objects immutable for a defined retention period, preventing them from being modified or deleted. This provides an important foundation for protecting backup data and other information that must remain unchanged. However, cyber resilience extends beyond immutability. Storage platforms should also be evaluated for capabilities across identity, access, network security, encryption, administrative protection, monitoring and infrastructure architecture. Scality addresses these requirements through its CORE5 cyber resilience model, which applies multiple levels of protection across the storage system from API to architecture. Capabilities across Scality platforms include S3 Object Lock, identity and access controls, multi-factor authentication and encryption. For organizations evaluating on-prem object storage as a backup target, this broader security architecture should be a significant consideration. 4. Durability and availability Large object repositories may contain years of business-critical information. Protecting that data requires an architecture capable of tolerating hardware failures without compromising integrity or availability. Enterprise object storage commonly uses technologies such as erasure coding, replication and automated self-healing to distribute and protect data across infrastructure. Scality RING is designed around a distributed architecture using data protection mechanisms including erasure coding, replication and self-healing. It can also distribute data geographically for environments that require resilience across multiple sites or availability zones. The relevant question is therefore not simply how much data a platform can store. Enterprises should examine what happens when disks, servers, racks or entire locations become unavailable and how the system maintains access and restores protection. 5. Non-disruptive growth and operations Storage environments can remain in production far longer than individual server generations. The best on-prem object storage should therefore support infrastructure expansion, hardware refreshes and software upgrades without requiring regular periods of planned disruption. A scale-out software architecture can allow newer hardware generations to enter the environment while older infrastructure is gradually retired. This is particularly useful for multi-petabyte environments, where migrating an entire dataset during every infrastructure refresh would be costly and operationally difficult. 6. Hardware choice Hardware flexibility is another consideration when comparing software-defined and appliance-based object storage. A software-defined platform can give organizations greater choice over server configurations and infrastructure vendors while allowing storage software to evolve separately from the hardware lifecycle. Scality RING is 100% software-defined, allowing organizations to deploy storage on standard server infrastructure rather than requiring a proprietary storage appliance. This approach can also help organizations take advantage of improvements in drive density, processing capability, power efficiency and hardware economics over the lifetime of the storage environment. 7. Support for multiple workloads Object storage increasingly serves as shared data infrastructure rather than infrastructure dedicated to a single application. A large enterprise deployment might support backup today and later expand to archives, analytics, AI or application data. Platforms capable of supporting multiple workloads can help reduce storage silos and allow organizations to consolidate large unstructured datasets around a common architecture. Scality RING supports both object and file storage and is designed for use cases including backup, archives, analytics, media, medical imaging, private cloud and AI data pipelines. 8. Hybrid-cloud capabilities Choosing on-prem storage does not require rejecting public cloud infrastructure. Many enterprises operate hybrid architectures in which some data remains under direct organizational control while other datasets or applications use public cloud services. An on-prem object storage platform should therefore be evaluated for its ability to participate in broader hybrid-cloud data strategies. S3 compatibility provides an important foundation because applications can interact with object storage through a consistent model across on-prem and cloud environments. Data management and replication capabilities can further support architectures that span sites, private clouds and public cloud services. Scality RING for large-scale on-prem object storage For organizations evaluating the best on-prem object storage for large enterprise environments, Scality RING is designed around scale, infrastructure flexibility and long-term operational resilience. RING provides software-defined file and object storage for environments where datasets can reach petabyte and exabyte scale. Key capabilities include: S3-compatible object storage Scale-out architecture Unified file and object storage Hardware independence Erasure coding and replication Automated self-healing S3 Object Lock Encryption Identity and access controls Multi-site and geographic deployment options Hybrid-cloud capabilities CORE5 cyber resilience These characteristics make RING particularly relevant when an organization expects its storage environment to support large or unpredictable growth across multiple workloads. Scality ARTESCA for cyber-resilient backup storage Not every organization needs an exabyte-scale storage environment. For backup teams seeking straightforward S3 object storage with strong ransomware protection, Scality ARTESCA provides a different operating model. ARTESCA is designed for immutable, cyber-resilient backup storage and can be deployed on standard servers or virtual machines. It integrates with major enterprise backup applications and supports S3 Object Lock for immutable backup repositories. ARTESCA can start with a relatively small deployment and grow as backup capacity increases, making it appropriate for organizations that want enterprise object storage capabilities without beginning with a large infrastructure footprint. The distinction matters when choosing on-prem object storage. The best platform should match the scale and workload being deployed rather than forcing every environment into the same architecture. Scality ADI for AI-scale data infrastructure AI is creating another class of on-prem object storage requirements. Organizations running large AI environments may need to combine multi-petabyte or exabyte capacity with high-performance access, cyber resilience, autonomous operations and control over where AI data resides. Scality ADI extends Scality’s distributed object storage foundation for these environments. It is designed around autonomous operations, flexible storage media and the performance requirements of enterprise AI infrastructure. This gives organizations another option when the primary storage requirement extends beyond conventional capacity-oriented object storage into large-scale AI data infrastructure. On-prem object storage vs. public cloud object storage Neither deployment model is universally better. The decision depends on workload characteristics and organizational priorities. Public cloud object storage can be attractive when organizations need immediate capacity, global cloud services or infrastructure without local deployment and management. On-prem object storage may be better aligned when organizations prioritize: Direct control of data and infrastructure Data sovereignty or residency Predictable long-term storage costs High-volume local data access Avoidance of recurring egress costs Integration with on-prem compute Large backup repositories Private AI infrastructure Long-term retention of large datasets Many enterprises will ultimately use both. The more useful question is which datasets belong in each environment and whether the underlying storage architecture gives teams enough flexibility to make those decisions based on workload requirements. How to choose an on-prem object storage platform Before selecting a platform, organizations should define what the environment needs to support today and how those requirements could change over its expected lifetime. Key questions include: How large will the environment become? Consider expected capacity over several years rather than only initial deployment size. Which workloads will use the storage? Backup, AI, archive and application workloads can have very different performance and operational requirements. How important is S3 compatibility? Identify the applications and specific S3 capabilities they require. What level of cyber resilience is required? Evaluate protection beyond immutability, including identity, network, administrative and architectural controls. What failures must the system tolerate? Consider disks, servers, racks, sites and geographic outages. Are there sovereignty requirements? Determine where data, metadata and associated infrastructure are permitted to reside. How will the platform scale? Understand whether capacity and performance can grow without disruptive migrations. What does the long-term cost model look like? Include infrastructure, operations, support, power, hardware refreshes and data movement. How much hardware flexibility is required? Determine whether the organization wants software-defined infrastructure or a fixed appliance model. Could additional workloads use the platform later? Consolidation can change the economics of an object storage investment considerably. These questions provide a more useful basis for comparison than a simple capacity or price-per-terabyte calculation. Why Scality is a strong choice for on-prem object storage Scality has focused on distributed object storage for enterprise and service-provider environments where scalability, resilience and long-term data control are core requirements. Its portfolio provides different approaches depending on the workload: RING for large-scale file and object storage, ARTESCA for cyber-resilient backup storage, and ADI for organizations building AI-scale data infrastructure. Across those environments, the common architectural priorities are S3-based data access, software-defined deployment, cyber resilience, scalability and organizational control over data. For enterprises evaluating the best on-prem object storage, those capabilities provide a practical framework for deciding which platform can support both current requirements and future growth. The right choice ultimately depends on the workload, scale, security requirements and operating model. For organizations that want to retain direct control of large unstructured datasets while using a modern S3 storage architecture, Scality provides options spanning backup environments through petabyte- and exabyte-scale enterprise infrastructure.
