Traditional SAS (Serial Attached SCSI) drives typically come in 10K or 15K RPM variants, while Nearline SAS (NL-SAS) or Midline (MDL) SAS drives operate at 7.2K RPM. The key distinction lies in their design philosophy:

// Example storage tier configuration using Python
storage_tiers = {
    "performance_tier": {
        "type": "SAS_15K",
        "interface": "12Gbps SAS",
        "latency": "2-3ms",
        "use_case": "OLTP databases"
    },
    "capacity_tier": {
        "type": "NL-SAS",
        "interface": "6Gbps SAS",
        "latency": "7-10ms", 
        "use_case": "Backup/archival"
    }
}

15K SAS drives typically offer:

• Higher IOPS (180-210 random read IOPS per drive)
• Lower latency (2-3ms average)
• Smaller capacities (300GB-900GB range)
• 5x higher AFR (Annualized Failure Rate) than NL-SAS

NL-SAS drives provide:

• Larger capacities (4TB-16TB common)
• Better $/GB ratio
• Power consumption about 40% lower
• Designed for 24/7 operation with 550TB/year workload

Throughput benchmarks show significant differences:

# Disk performance test results (fio output samples)
SAS_15K_900GB = {
    "randread": "175 IOPS",
    "randwrite": "165 IOPS",
    "seqread": "210 MB/s",
    "seqwrite": "195 MB/s"
}

NL_SAS_8TB = {
    "randread": "80 IOPS", 
    "randwrite": "75 IOPS",
    "seqread": "190 MB/s",
    "seqwrite": "185 MB/s"
}

SAS 10K/15K drives excel in:

• Database transaction logs
• Virtual machine swap files
• High-frequency trading systems

NL-SAS drives are better suited for:

• Backup targets
• Cold storage tiers
• Media repositories
• Compliance archives

When designing hybrid storage arrays, consider these factors:

// Sample ZFS pool configuration mixing drive types
zpool create -f tank \
    mirror c1t0d0 c1t1d0 \      # SAS 15K for metadata
    raidz2 c2t0d0 c2t1d0 c2t2d0 \  # NL-SAS for bulk storage
    cache c3t0d0                  # SSD for L2ARC

Enterprise storage systems like NetApp's FAS series automatically tier data between SAS and NL-SAS based on access patterns.

A typical 3PAR configuration shows:

• All-SAS array: $85,000 for 20TB @ 25,000 IOPS
• Hybrid array: $45,000 for 60TB @ 18,000 IOPS
• All-NL-SAS: $28,000 for 120TB @ 6,000 IOPS

The choice depends on workload characteristics and budget constraints. Modern auto-tiering solutions can dynamically move hot data to faster SAS tiers while keeping colder data on NL-SAS.

When architecting storage solutions, the choice between traditional SAS (Serial Attached SCSI) and Nearline/MDL (Midline) SAS drives significantly impacts performance and cost. High-performance SAS drives typically operate at 10K or 15K RPM speeds, while Nearline SAS variants run at 7.2K RPM with higher density.

The key technical distinctions include:

// Sample storage configuration comparison
const driveSpecs = {
  highPerfSAS: {
    rpm: 15000,
    interface: "SAS-12Gbps",
    avgLatency: "2.0ms",
    mtbf: "2.0M hours"
  },
  nearlineSAS: {
    rpm: 7200,
    interface: "SAS-6Gbps",
    avgLatency: "4.16ms",
    mtbf: "1.4M hours"
  }
};

Real-world performance testing shows significant IOPS differences:

// IOPS comparison calculator
function calculateIOPS(rpm, seekTime) {
  const rotationalLatency = 60000 / rpm / 2;
  return 1000 / (seekTime + rotationalLatency);
}

const highPerfIOPS = calculateIOPS(15000, 2.0);
const nearlineIOPS = calculateIOPS(7200, 4.16);

High-Performance SAS:
- Database transactional systems
- Virtual machine storage
- High-frequency trading platforms

Nearline SAS:
- Archival storage
- Backup repositories
- Cold data storage solutions

A typical enterprise storage array might mix both types:

// Storage tier configuration example
storageTier = {
  tier1: {
    type: "SAS-15K",
    capacity: "10TB",
    cost: "$8,000"
  },
  tier2: {
    type: "NL-SAS",
    capacity: "50TB",
    cost: "$10,000"
  }
};

Major storage vendors implement these differently:

• Dell EMC PowerStore: Auto-tiering between SAS and NL-SAS
• NetApp FAS: Uses NL-SAS for capacity-optimized aggregates
• HPE Nimble: Predictive analytics for data placement

Field data shows annual failure rates:

// AFR calculation based on Backblaze data
afrData = {
  enterpriseSAS: 0.8,  // 0.8% AFR
  nearlineSAS: 1.2     // 1.2% AFR
};