Enterprise Storage: NAS, SAN, DAS and Object, Matched to the Workload
Enterprise storage is the set of systems that store, protect and serve an organisation's data. It covers block storage (SAN) for databases and virtual machines, file storage (NAS) for shared and unstructured data, direct-attached storage (DAS) for single servers, and object storage for backups, archives and data at massive scale, along with the services that keep that data safe: snapshots, replication, deduplication and tiering.
Data keeps growing faster than storage budgets, and AI has added a new kind of demand: datasets that must be read quickly and repeatedly to keep GPUs working. Choosing the wrong storage is expensive either way. Over-provision and you pay for capacity nobody needs; under-provision and applications slow down while the cause is hard to see.
The Four Types of Enterprise Storage
Most enterprises run more than one type, chosen by how the application reads and writes data. The table below sets out where each one fits.
| Type | How it is accessed | Best for | Protocols |
|---|---|---|---|
| SAN (block) | Block-level, over a dedicated storage network | Databases, virtualisation, latency-sensitive apps | Fibre Channel, iSCSI, NVMe-oF |
| NAS (file) | File-level, over the network | Shared files, home directories, unstructured data | NFS, SMB |
| DAS (direct) | Block-level, attached straight to one server | Single-server, high-speed local workloads | SAS, NVMe |
| Object | Through an API, in a flat namespace | Backups, archives, cloud-native data, massive scale | S3 |
All-Flash, Hybrid or Object: Choosing by Media
Once the type is settled, the media decides cost and speed. The table below shows the trade-off.
| Media | Performance | Cost per TB | Best for |
|---|---|---|---|
| All-flash (NVMe) | Very low latency, highest throughput | Highest | Databases, virtualisation, AI, latency-sensitive apps |
| Hybrid (flash + disk) | Mixed: flash for hot data | Medium | General workloads where capacity matters as much as speed |
| Scale-out | High throughput, grows to petabytes | Medium | Unstructured data, file at scale, AI datasets |
| Object | High capacity, massive scale | Lowest | Backups, archives, cloud-native data, long-term retention |
NVMe all-flash arrays suit workloads where latency is the bottleneck. Scale-out file and object platforms grow to petabytes for unstructured data and AI. Hybrid and object tiers keep the cost of long-retention data under control.
Why Enterprise Storage? Why It Matters Now
- The right type for the workload: SAN, NAS, DAS or object, matched to how data is read and written.
- Flash where it counts: NVMe all-flash for latency-sensitive databases and virtualisation, hybrid where capacity matters more.
- Ready for AI: scale-out, high-throughput storage that keeps GPU clusters fed.
- Ransomware resilience: immutable snapshots and replicated copies, so recovery is a restore, not a rebuild.
- Lower cost per terabyte: deduplication, compression and tiering reduce the capacity you pay for.
- Grows without disruption: scale-out and non-disruptive upgrades avoid forklift replacements.
Storage is the layer that quietly decides application performance. A database on the wrong storage runs slowly however fast the server is, and an AI job on storage that cannot keep up wastes costly GPU time. The array rarely fails outright; it simply throttles everything that depends on it.
Indian Digital Systems sizes storage to the workload and the growth ahead, choosing between all-flash, hybrid, scale-out or object on Dell EMC and NetApp, and building protection into the design from the start.
Storage for AI Workloads
AI changes what storage has to do. Training reads huge datasets again and again, and a storage tier that cannot keep up leaves a costly GPU cluster waiting. Inference needs low latency and data pipelines that deliver fresh data on time.
Feeding GPUs takes high-throughput, scale-out storage, ideally with a data path that avoids bottlenecks between the array and the GPUs. We design the storage tier alongside the compute so utilisation stays high and training finishes sooner.
Protecting Data: Snapshots, Replication and Cyber Resilience
Storage is also the last line of defence against data loss. Snapshots capture the state of data at a point in time; replication keeps a copy at another site; immutable and isolated copies cannot be changed or deleted, even by an attacker with stolen credentials.
The aim is a short, rehearsed recovery. We build these layers into the storage design and test the restore, so a failure or an attack becomes a managed recovery rather than a crisis.
Enterprise Storage Across India: Why the Workload Decides the Design
Indian enterprises do not store data the same way. A GCC standardising storage across sites has a different problem from a bank under retention rules, or a manufacturer consolidating decades of scattered file shares onto one platform.
Data growth, residency and retention rules, mixed legacy estates and tight budgets all shape the design. For manufacturing, BFSI, healthcare, IT and ITeS and GCC environments, we choose the storage by what the data needs, and keep it protected and available in-country where regulation requires.
Indian Digital Systems: The Partner That Designs, Delivers, and Protects
Buying an array is easy. Sizing storage to the workload, migrating data without downtime and protecting it against failure and attack is where experience matters.
We bring over 32 years of enterprise infrastructure delivery and certified engineers. We design and deliver storage on Dell EMC and NetApp, across all-flash, hybrid, scale-out and object, with data protection and recovery built in.
Storage is one layer of the data center. It works alongside AI Infrastructure, Compute Solutions, Converged and Hyperconverged Infra, Data Protection and Cyber Recovery and Data Center Networking, so capacity, performance and protection are planned together.
From assessment and sizing through migration and ongoing support, we build storage that keeps data fast, safe and ready for what comes next.