Data Management Glossary
Data Storage Costs
Data storage costs are the expenses associated with storing and maintaining data in various forms of storage media, such as hard drives, solid-state drives (SSDs), cloud storage, and tape storage. These costs can be influenced by a variety of factors, including the size of the data, the type of storage media used, the frequency of data access, and the level of redundancy required. As the amount of unstructured data generated continues to grow, the cost of storing it remains a significant consideration for many organizations. A few years ago, the Komprise State of Unstructured Data Management Report found that the majority of enterprise IT organizations are spending over 30% of their budget on data storage, backups and disaster recovery. This is why shifting from storage management to storage-agnostic data management continues to be a topic of conversation for enterprise IT leaders.
In the 2024 report the top priorities for data storage include cost optimization (54%), preparing for AI (51%) and investing in data management and data mobility (41%).
Read the latest Komprise State of Unstructured Data Management Report.
Cloud Data Storage Costs
Cloud data storage costs refer to the expenses incurred for storing data on cloud storage platforms provided by companies like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). In addition to the points above about data storage costs (amount of data stored and frequency of data access) in the cloud the level of durability and availability required are also factors when it comes to cloud storage costs. Cloud data storage providers typically charge based on the amount of data stored per unit of time, and additional fees may be incurred for data retrieval, data transfer, and data processing. Many cloud storage providers offer different storage tiers with varying levels of performance and cost, allowing customers to choose the option that best fits their budget and performance needs. With the right cloud data management strategy, cloud storage can be more cost-effective than traditional hardware-centric on-premises storage, especially for organizations with large amounts of data and high storage needs.
Managing Data Storage Costs
Managing data storage costs involves making informed decisions (and the right investment strategies) about how to store, access, and use data in a cost-effective manner.
Read the interview with Komprise Field CTO Benjamin Henry: Is there any relief from data storage costs?
Here are some strategies for managing data storage costs:
- Data archiving: Archiving infrequently accessed data to lower cost storage options, such as object storage or tape, can help reduce storage costs.
- Data tiering: Using different storage tiers for different types of data based on their access frequency and importance can help optimize costs.
- Compression and deduplication: A well known data storage technique, compressing data and deduplicating redundant data can help reduce the amount of storage needed and lower costs.
- Cloud file storage: Using cloud storage can be more cost-effective than traditional on-premises storage, especially for organizations with large amounts of data and high storage needs.
- Data lifecycle management (aka Information Lifecycle Management): Regularly reviewing and purging unneeded data can help control storage costs over time.
- Cost monitoring and optimization (see cloud cost optimization): Regularly monitoring and analyzing data storage costs and usage patterns can help identify opportunities for cost optimization.
By using a combination of these strategies, organizations can effectively manage their data storage costs and ensure that they are using their data storage resources efficiently. Additionally, organizations can negotiate with data storage providers to secure better pricing and take advantage of cost-saving opportunities like bulk purchasing or long-term contracts.
Read: Storage Prices are Doubling: How IT Teams are Responding.
Why are data storage costs increasing right now?
Data storage costs are rising due to a global surge in demand for memory and flash storage driven largely by AI infrastructure. Enterprise SSD prices and NAND flash components have increased sharply as data centers compete for limited supply, with some forecasts showing enterprise SSD prices rising more than 50% in a single quarter and NAND flash costs increasing dramatically since 2025.
As AI workloads expand and hyperscale data centers secure large portions of global memory production, enterprises are facing higher storage costs and longer hardware procurement cycles.
How do rising memory and flash prices impact enterprise storage budgets?
Rising memory prices directly increase the cost of enterprise storage systems such as high-performance NAS and all-flash arrays. In some cases, enterprise SSD costs have surged dramatically compared with traditional disk storage, forcing organizations to rethink storage architectures and budgets.
As a result, many IT teams are prioritizing strategies such as data tiering, capacity optimization, and hybrid storage architectures to control infrastructure spending.
Why is storage efficiency becoming a strategic priority for IT teams?
As storage hardware prices rise, organizations must focus on using expensive primary storage more efficiently. Without visibility into data usage, large volumes of inactive files can accumulate on high-performance systems, increasing costs and accelerating storage refresh cycles.
By identifying cold data and moving it to lower-cost storage tiers, organizations can reduce infrastructure costs while keeping active storage optimized for performance workloads.
How does unstructured data management help organizations control rising storage costs?
Unstructured data management helps organizations analyze file and object storage environments to identify inactive data, duplicates, and growth trends. With this visibility, IT teams can automatically tier cold data to lower-cost storage and reclaim expensive primary storage capacity.
This approach allows organizations to delay costly storage purchases, extend the lifespan of existing infrastructure, and keep high-performance storage focused on active workloads.
Read: The Memory ‘Crisis’ Is An Opportunity for a Smarter Unstructured Data Strategy
Why is data tiering especially important during periods of rising storage prices?
When storage prices increase, inefficient storage architectures become significantly more expensive. Data tiering helps organizations minimize the amount of data that must remain on costly high-performance systems by transparently moving inactive files to lower-cost object or cloud storage.
By shrinking the active storage footprint, organizations can reduce capital spending and better control infrastructure costs during storage refresh cycles.
Stop Overspending on Data Storage with Komprise
The blog post How Storage Teams Use Komprise Deep Analytics summarizes a number of strategies storage teams use Komprise Intelligent Data Management to deliver greater data storage cost savings and unstructured data value to the business, including:
- Business unit metrics with interactive dashboards
- Business-unit data tiering, retention and deletion
- Identifying and deleting duplicates
- Mobilizing specific data sets for third-party tools
- Using data tags from on-premises sources in the cloud
In the blog post Quantifying the Business Value of Komprise Intelligent Data Management, we review a storage cost savings analysis that saves customers an average 57% of overall data storage costs and over $2.6M+ annually. In addition to cost savings, benefits include:
Plan Future Data Storage Purchases with Visibility and Insight
With an analytics-first approach, Komprise delivers visibility into how data is growing and being used across a customer’s data storage silos – on-premises and in the cloud. Data storage administrators no longer have to make critical storage capacity planning decisions in the dark and now can understand how much more storage will be needed, when and how to streamline purchases during planning.
Optimize Data Storage, Backup, and DR Footprint
Komprise reduces the amount of data stored on Tier 1 NAS, as well as the amount of actively managed data—so customers can shrink backups, reduce backup licensing costs, and reduce DR costs.
Faster Cloud Data Migrations
Auto parallelize at every level to maximize performance, minimize network usage to migrate efficiently over WANs, and migrate more than 25 times faster than generic tools across heterogeneous cloud and storage with Elastic Data Migration.
Reduced Datacenter Footprint
Komprise moves and copies data to secondary storage to help reduce on-premises data center costs, based on customizable data management policies.
Risk Mitigation
Since Komprise works across storage vendors and technologies to provide native access without lock-in, organizations reduce the risk of reliance on any one storage vendor.
Deliver the Right Data to AI
AI outcomes depend on the quality and relevance of the data. Komprise identifies, classifies, and curates the right unstructured datasets across hybrid storage without requiring data migration or disruption. Eliminate the bottlenecks of traditional ETL and moves only the data you need, directly in native format, so you can feed AI/ML pipelines faster and avoid vendor lock-in. Learn more about Smart Data Workflows.
