Most of the data organizations produce no longer lives in database tables; it sits in scanned documents, images, video recordings, log files and backups. This kind of unstructured data is growing fast in volume and is straining traditional storage approaches in terms of both cost and manageability.

Object storage became widespread with the cloud providers as an answer to this problem; today it has also become a standard architectural component in on-premise data centres. In this article we look at what object storage is, when it is the right choice, and how it should be positioned within a sound data management strategy.

We covered the overall framework of a storage strategy earlier in our article How Safe Is Your Data? This article focuses on an important piece within that framework.

Strategy First: Why Data Management Comes Before Storage

The question most often asked in storage projects is "How much capacity do we need?" The right question, however, is "Which data do we need to keep, for how long, with what access speed and at what level of protection?"

Investments made without answering that question usually end in one of two outcomes: either all data is kept on the most expensive tier, or critical data is left without adequate protection. A good data management strategy starts with three fundamental decisions:

• Classification: The business importance of the data, its confidentiality level and its legal retention obligations. Personal data under KVKK (Türkiye's Personal Data Protection Law), financial records and operational logs cannot be managed by the same rules.
• Lifecycle: When data turns from frequently accessed "hot" data into rarely opened "cold" data, and when it should be securely destroyed.
• Access model: Whether the data will be read by an application within milliseconds, or whether retrieving it within minutes when needed is sufficient.

Block, File and Object: Three Storage Models

The easiest way to understand object storage is to compare it with the other two models:

• Block storage: Stores data in fixed-size blocks. It offers low latency and high performance, making it ideal for databases and virtual machines. Its cost, however, rises quickly as it scales.
• File storage: Organizes data in a hierarchy of folders and files. It is the model users are familiar with and suits shared workspaces. Once millions of files are reached, though, managing the hierarchy becomes difficult.
• Object storage: Stores each piece of data as an independent "object" made up of the data itself, rich metadata and a unique identifier. There is no folder hierarchy; objects are kept in a flat structure and accessed through HTTP-based interfaces.

These models are not competitors but complements. In a healthy infrastructure, each one takes on the job it does best.

What Makes Object Storage Powerful

Virtually Unlimited Scalability

Thanks to the flat structure, capacity grows by adding new nodes to the existing system. Moving from terabytes to petabytes is possible without changing the architecture.

Smarter Management Through Metadata

Custom tags such as document type, creation date, retention period or owning department can be attached to each object. This makes it easier to search, classify and manage data with automated rules.

Immutability Against Ransomware

The object lock feature prevents an object from being deleted or modified for a defined period, including by accounts with administrator privileges. Combined with versioning, it forms one of the most effective layers of defence against ransomware. This is why object storage is increasingly chosen as the target storage in modern backup architectures.

Efficient Data Protection

Rather than replicating full copies of data, object storage systems typically use erasure coding. Data is split into fragments and distributed, together with parity information, across different disks and nodes. Data remains protected even when several disks or nodes are lost, while consuming far less raw capacity than full replication.

A Standard Access Interface

S3-compatible APIs have become the de facto industry standard. This means an object storage infrastructure built on-premise can work directly with backup software, analytics platforms and modern applications, and can easily extend to hybrid scenarios with the cloud when needed.

When Object Storage Is Not the Right Choice

Like every technology, object storage has its limits. For the following workloads, block or file storage is usually the better option:

• Transaction-heavy databases that require low latency
• Applications that constantly update small portions of a file
• Legacy applications that do not support the S3 interface and expect a file system

The right architecture places each workload on the right tier, rather than trying to force the workload to fit a storage model.

Typical Use Cases

• Backup and archive: An immutable backup target and a long-term retention tier.
• Digital archives and document management: Storing scanned documents, contracts and institutional memory in a form that is searchable through metadata.
• Media and video: Security camera recordings, training videos and visual content libraries.
• Data lakes and analytics: Keeping the raw datasets that feed artificial intelligence and data platforms cost-effectively.
• Log and compliance data: Protecting records that must be retained for years under regulation in an immutable form.

Five Questions to Ask Before You Start

• How much of our data is hot and how much is cold? Have we measured that ratio?
• Which of our applications support S3-compatible access, and which need an intermediate layer?
• Are our legal retention periods defined, and can they be turned into automated lifecycle rules?
• Do our backups currently sit on an immutable target?
• Do we have a clear policy on whether data should be kept on-premise, in the cloud or in a hybrid model?

The ORBISIS Approach: A Data Map Before Capacity

At ORBISIS we begin storage projects not with a capacity calculation but by mapping the organization's data. Once we have determined which data will be kept on which tier, at what level of protection and for how long, we design block, file and object storage as a single whole. The experience we have gained, from petabyte-scale public archive projects to enterprise backup transformations, shows us that a well-designed data management strategy both lowers cost and ensures the data is genuinely protected.

Deciding how data should be stored is only half the job. Next week we will address the other half, namely where data should reside, under the heading of hybrid cloud and data sovereignty.

To review your data management and storage infrastructure together, explore our Data Center and Infrastructure Solutions and Cloud and Hybrid IT Solutions pages, or get in touch with our expert team.