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ARCHITECTURAL BLUEPRINT #83 • DATABASE PERFORMANCE & MEMORY TIERING

SAP HANA Native Storage Extension (NSE), Data Aging & Tiering: Clean Core Architecture Guide

How enterprise architects optimize SAP HANA memory footprints without sacrificing analytical query performance. Master Native Storage Extension (NSE), page-loadable column store partitions, buffer cache tuning, and ILM cold storage.

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1. The HANA Memory Scaling Challenge

In massive enterprise deployments, tables like ACDOCA (Universal Journal), MATDOC (Material Documents), and change log tables (CDPOS) routinely reach hundreds of millions or billions of rows. Keeping 100% of these records in expensive main memory (DRAM) leads to skyrocketing cloud hyperscaler costs and multi-terabyte hardware upgrades.

SAP HANA Native Storage Extension (NSE) solves this by introducing a built-in, multi-temperature data tiering engine that allows historical data to reside on fast NVMe SSD storage in page-loadable format, occupying DRAM only when explicitly queried.

2. Multi-Temperature Architecture: Hot vs. Warm vs. Cold

Tier Storage Medium Typical Age HANA Memory Footprint Access Latency
Hot Tier Main In-Memory DRAM Current + Previous Year 100% in DRAM (Columnar) Sub-millisecond
Warm Tier (NSE) NVMe SSD + NSE Buffer Cache 2 to 7 Years 10-15% in Buffer Cache Low milliseconds (Page Fault)
Cold Tier (ILM) Cloud Object Storage (S3/Azure Blob) > 7 Years (Statutory) 0% in HANA Memory Seconds (Nearline Archive)

3. Range Partitioning with NSE (ACDOCA Best Practice)

The most robust architectural pattern is applying NSE at the partition level. A table is partitioned by Fiscal Year (GJAHR). Recent partitions remain hot, while historical partitions are marked PAGE LOADABLE:

-- Alter historical partition for ACDOCA to Page Loadable ALTER TABLE "ACDOCA" ALTER PARTITION 1 PAGE LOADABLE; -- Verify load status in system views SELECT TABLE_NAME, PART_ID, LOAD_UNIT, ESTIMATED_MEMORY_SIZE_IN_TOTAL FROM M_CS_PARTITIONS WHERE TABLE_NAME = 'ACDOCA';

4. Sizing and Tuning the NSE Buffer Cache

When queries access page-loadable records, SAP HANA reads pages into the dedicated NSE Buffer Cache. Best practice sizing:

💡 NSE Sizing Rules of Thumb

1. Cache Size: Allocate 10% to 15% of total system DRAM to buffer_cache_cs.

2. Cache Hit Ratio: Monitor M_CS_NSE_BUFFER_CACHE_STATISTICS; maintain a hit ratio > 95%.

3. Query Pruning: Ensure custom CDS views and RAP queries always pass fiscal year filters to avoid unnecessary cache eviction cycles.

5. Production Implementation Checklist

Follow these operational steps when implementing SAP HANA NSE in a Clean Core landscape:

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