SAP HANA Storage: Designing and Optimizing Storage for Modern In-Memory Analytics

In-memory databases have transformed how organizations analyze data, delivering fast insights and real-time decision support. Central to that capability is how data is stored, persisted, and accessed. SAP HANA storage choices influence performance, reliability, and total cost of ownership. This article provides a practical overview of SAP HANA storage, covering architecture, tiering strategies, sizing considerations, and best practices to help you design a robust storage foundation for SAP HANA storage workloads.

Understanding SAP HANA Storage Architecture

At its core, SAP HANA storage refers to how data and logs are persisted on disk and how they interact with the in-memory data engine. Although SAP HANA keeps most hot data in memory for fast analytics, durability and recoverability rely on a carefully designed storage layout. The main components are data volumes, log (redo) volumes, and the persistence layer that coordinates between memory and disk.

Data volumes hold the actual database files that represent the physical state of your SAP HANA storage. These are structured to support efficient in-memory columnar storage, compression, and fast I/O.
Log volumes store redo logs and undo-related information. They are critical for crash recovery and ensure data integrity in the event of a failure. High write throughput and low latency are essential for log storage.
Backup and archive storage provide long-term durability beyond the day-to-day operations. These targets may reside on local disks, network-attached storage, or cloud-based repositories, but they feed SAP HANA storage strategies for recovery and retention goals.

In modern deployments, SAP HANA storage is often implemented with a mix of storage media, including NVMe SSDs for high IOPS, SATA or SAS SSDs for capacity, and, in some cases, persistent memory (PMEM) hardware to accelerate persistence and startup times. The resulting storage architecture should balance performance with cost, keeping hot data in fast tiers while colder data can be migrated to more economical storage options.

Data Volumes, Log Volumes, and Tiering

Allocating data and log volumes across dedicated disks is a foundational best practice for SAP HANA storage. Separating data and log I/O helps prevent resource contention and improves overall throughput. For many workloads, a typical pattern is to place data volumes on high-performance solid-state drives and log volumes on equally reliable, low-latency storage to minimize write amplification and latency spikes.

Tiered storage strategies extend this idea to balance performance and cost. There are several approaches:

Dynamic Tiering: This feature allows larger, colder data sets to reside on disk-based storage while keeping hot data in memory. It enables SAP HANA storage to scale beyond the capacity of RAM, while preserving fast analytics for frequently accessed data.
Native Storage Extension (NSE): NSE lets you leverage external storage as an extension of SAP HANA storage for older or less frequently accessed data. This approach can lower total cost of ownership while maintaining query capabilities through smart data management.
Hybrid configurations: Some deployments mix on-premises flash with cloud-based storage or object stores for backups and archives. This can provide resilience and elasticity without compromising day-to-day analytics.

When configuring SAP HANA storage, it is essential to plan the storage layout to avoid bottlenecks. For example, ensure that enough bandwidth is available for log writes, and that data volumes do not become a single point of contention. Regular monitoring helps detect I/O wait times, saturation, or disk failures that could jeopardize SAP HANA storage performance.

Sizing and Capacity Planning for SAP HANA Storage

Accurate sizing of SAP HANA storage components reduces risk and delivers predictable performance. Capacity planning should consider current data volume, growth projections, backup retention, and the specific data retention policies that affect SAP HANA storage needs.

RAM vs. disk balance: In SAP HANA storage terms, ensure the in-memory footprint remains within your physical RAM while keeping a robust on-disk persistence layer. Data compression and the columnar store can reduce RAM requirements, but dependable storage capacity remains necessary for persistence and backups.
Data growth and aging: Anticipate growth over 3–5 years, including peak workloads. Tiering strategies can help keep the most active data in fast storage while older data migrates to NSE or cloud backups.
Backup window planning: SAP HANA storage design should account for backup frequency and restore objectives. Sufficient storage for full and incremental backups, plus offsite replication, is vital for recovery objectives.

Practical sizing guidelines depend on workload characteristics, but a common rule is to allocate ample space for data volumes to accommodate compression ratios, alongside dedicated logs with ample headroom for peak write bursts. Regularly revisiting these numbers during quarterly capacity reviews helps keep SAP HANA storage aligned with usage patterns.

Best Practices for SAP HANA Storage Performance

To maximize SAP HANA storage performance, follow these best practices. They focus on minimizing latency and ensuring consistent throughput for both data and log I/O, while preserving data integrity.

Separate data and log volumes: Isolate I/O paths to reduce contention and improve predictability of SAP HANA storage performance.
Use high-performance storage for hot data: NVMe SSDs or enterprise-grade SSDs deliver the IOPS SAP HANA storage needs during analytics and reporting workloads.
Optimize file system and OS settings: Align block size, enable large pages, and tune I/O schedulers for database workloads. Proper OS configuration reduces latency and improves throughput.
Implement redundancy and failover: Use RAID configurations or equivalent storage replication to protect SAP HANA storage data and logs. Consider high-availability configurations to minimize downtime.
Monitor proactively: Leverage SAP HANA Cockpit, SAP HANA Studio, or other monitoring tools to track I/O latency, disk saturation, and backup health. Alerts help catch SAP HANA storage issues before they impact users.
Plan for backups and restores: Regular backups ensure data durability. Test restores periodically to validate SAP HANA storage recovery procedures and performance.
Document the storage topology: Maintain up-to-date diagrams that show data and log volumes, storage targets, and any tiering rules. Clear documentation helps operations teams troubleshoot SAP HANA storage problems quickly.

With SAP HANA storage, performance is not only about raw speed. It is about a well-architected blend of fast data paths, resilient persistence, and scalable capacity that aligns with business needs. The storage strategy should evolve with the analytics workload, data volume, and modernization goals.

Backup, Recovery, and High Availability Considerations

Reliable SAP HANA storage requires an integrated approach to backup and recovery. Regular backups protect against data loss, while a robust high-availability and disaster-recovery posture minimizes downtime. The storage design should accommodate multiple restore scenarios, from point-in-time recovery of specific data segments to full system restores following a failure.

Backups to external targets: Use network shares, object storage, or cloud repositories to offload backups away from primary SAP HANA storage. This reduces the risk of data loss from regional failures.
System Replication: SAP HANA System Replication provides near-zero RPO in failover scenarios by keeping a synchronized copy of the database on a secondary host. Storage design should support fast synchronization and consistent commit logs.
Point-in-time recovery: Maintain log integrity and ensure logs are accessible for precise recovery steps. SAP HANA storage must guarantee that logs are durable and recoverable.

When planning for SAP HANA storage in backup and recovery scenarios, consider data retention policies, legal and regulatory requirements, and business continuity objectives. A well-thought-out storage strategy ensures that data remains accessible and recoverable when it matters most.

Cloud and Hybrid Considerations for SAP HANA Storage

As many organizations adopt cloud or hybrid deployments, SAP HANA storage design must adapt to new environments. Cloud storage offers scalable capacity and flexible backups, while on-premises storage can deliver deterministic performance for critical workloads. In cloud-enabled SAP HANA storage environments, consider:

Latency characteristics between compute and storage: Choose cloud options that minimize cross-network latency for hot data.
Resilience and data residency: Ensure the storage architecture meets compliance and governance requirements.
Cost optimization: Use a tiered approach that places infrequently accessed data in lower-cost storage while preserving fast access for active analytics.

Hybrid strategies often combine on-premises high-performance storage for active workloads with cloud or NSE-based storage for scalability and cost efficiency. The SAP HANA storage design should be flexible enough to adapt to evolving data strategies without compromising performance or reliability.

Operational Readiness and Governance

A successful SAP HANA storage strategy combines technical excellence with strong operational discipline. Governance around change management, capacity planning, and incident response helps maintain stable performance over time. Regular audits of storage configurations, performance baselines, and recovery drills reinforce reliability.

Change control: Any changes to storage topology should follow a formal process with risk assessment and rollback plans.
Performance baselines: Establish and maintain baselines for I/O latency, throughput, and backup times to detect anomalies quickly.
Disaster recovery drills: Simulate failures and data loss scenarios to validate the effectiveness of SAP HANA storage configuration and backup strategies.

Ultimately, SAP HANA storage is a foundational element of a high-performing data platform. By combining thoughtful architecture, tiered storage options, robust backups, and proactive monitoring, organizations can unlock faster analytics, improved reliability, and greater resilience for their SAP HANA workloads.

Conclusion: A Practical Path to Optimized SAP HANA Storage

Designing and optimizing SAP HANA storage requires a clear view of data access patterns, growth trajectories, and business requirements. A well-planned SAP HANA storage architecture separates data and log I/O, leverages tiering to balance performance with cost, and includes robust backup and recovery practices. Whether you operate entirely on premises, migrate to the cloud, or pursue a hybrid approach, thoughtful storage design will help you sustain the fast, reliable analytics that SAP HANA storage makes possible. By aligning hardware choices with workload characteristics and maintaining disciplined operations, you can ensure that SAP HANA storage remains a strong enabler of business insights for years to come.