Persistent Memory vs RAM in 2025: CXL & NVDIMM-P Guide

Modern servers are fast. But not fast enough.

In 2025, DRAM delivers nanosecond latency—but costs a fortune per gigabyte and caps out quickly. SSDs offer terabytes of capacity—but with 100× slower access times. Somewhere between those extremes is a performance canyon that traditional hardware architectures haven’t bridged effectively.

That’s where persistent memory (PMEM) steps back into the spotlight.

With Intel Optane officially sunset, engineers are left asking:

What fills the gap between DRAM and NAND now?

The answer lies in two next-gen directions:

• NVDIMM-P: Persistent memory on the DDR5 memory bus
• CXL Type-3: Fabric-attached memory expansion over PCIe

Whether you’re optimizing SAP HANA restart times, compressing latency in VM caching, or prepping for composable memory fabrics, understanding PMEM’s role in your stack is no longer optional.

Persistent memory (PMEM) is a hybrid storage class that combines the speed of DRAM with the non-volatility of NAND. It behaves like memory—but keeps data even when the power is cut.

Unlike SSDs, PMEM is byte-addressable and connects directly to the memory controller—either via DIMM slots (like NVDIMM-P) or PCIe lanes (via CXL).

• Non-volatile (retains data across reboots)
• Lower latency than NAND (~100–500 ns vs 80,000+ ns)
• Higher capacity per socket than DRAM
• Byte-addressable, unlike block-based SSDs

Type	Interface	Example Products	Status
Intel Optane DCPMM	DDR4	P4800X, P5800X	Discontinued
NVDIMM-P	DDR5	Micron, Samsung prototypes	Sampling 2025
CXL Type-3 Devices	PCIe 5.0/6.0	Astera Labs, Samsung modules	Early deployment

Here’s a simplified memory-storage latency ladder for 2025:

Persistent memory slots into the “warm tier”—bridging the gap between fast but volatile DRAM and slow but persistent NAND.

While DRAM is the de facto standard for volatile system memory, persistent memory introduces a new tier with distinct tradeoffs. Here’s how they compare across critical technical and economic dimensions:

Metric	DRAM (DDR5 RDIMM)	Persistent Memory (PMEM)
Speed/Latency	80–100 ns	120–500 ns
Volatility	Volatile	Non-volatile
Endurance	Very High	Medium (20–60 DWPD)
Latency	Lowest	Moderate
Capacity per Module	32–128 GB	128–512 GB
Cost per GB	~€8/GB	~€3/GB

• DRAM: ~80–100 ns (reads/writes directly on memory bus)
• PMEM: ~120–500 ns depending on form factor (NVDIMM-P vs CXL)

PMEM is slower, but still orders of magnitude faster than SSDs. For workloads that tolerate minor latency penalties in exchange for capacity or persistence, it’s a strong fit.

• DRAM: Fully volatile — loses all data on power loss
• PMEM: Non-volatile — retains data across reboots and crashes

This enables fast restart use-cases (e.g., SAP HANA), and write-heavy systems that benefit from journaling or tiered memory management.

• DRAM: Practically infinite (10⁸–10⁹ cycles, wear is negligible)
• PMEM: Limited endurance (~60 DWPD for Optane-class; 20–40 DWPD expected for NVDIMM-P / CXL Type-3)

PMEM endurance sits between DRAM and SSDs, but high enough for most enterprise read/write cycles, especially when used as a cache or journaling layer.

• DRAM: Typically 32–64 GB per RDIMM; high-density 128 GB RDIMMs at a premium
• PMEM: 128 GB–512 GB per module (2025), higher with CXL pooling

This enables 2×–4× memory expansion per socket, especially valuable in data-intensive and virtualized environments.

• DRAM: ~€7–9/GB in Q2 2025
• PMEM: ~€2.5–4/GB (Optane-class); NVDIMM-P & CXL expected to drop below €3/GB at volume

Lower $/GB makes PMEM ideal for memory-bound workloads where cost-efficiency matters more than peak bandwidth.

Intel officially pulled the plug on its Optane product line in mid-2022, with the final production runs of P5800X SSDs and DCPMM (3D XPoint) memory modules wrapping up between 2023 and early 2024.

Event	Milestone
July 2022	Intel exits Optane business
Q1 2023	Final Optane orders accepted
Q3 2023	DCPMM EOL confirmed for all SKUs
Q1 2024	P5800X SSD supply enters depletion
2025	Secondary market remains, but support limited

If you’re still deploying Optane, expect the following risks:

• Sourcing issues: Only refurbished or old-stock units available
• Firmware gaps: BIOS/microcode support fading for new platforms
• Spare part availability: No new stock from Intel or official resellers
• Platform lock-in: Only works on specific Xeon CPUs (Cascade Lake, Cooper Lake, Ice Lake)

In short: Optane is not a viable long-term solution for new deployments.

• Leverage existing stock in “cold standby” failover nodes (non-critical roles)
• Use PMEM-aware file systems (like ext4-dax, xfs-dax) on SSDs to simulate persistent tier behavior
• Deploy NVMe-over-Fabrics + RAM caching to fill gaps until CXL/NVDIMM-P is production-ready

However, real long-term answers lie in NVDIMM-P and CXL Type-3 memory modules—covered in the next section.

With Intel Optane discontinued, two serious contenders have emerged to fill the persistent memory gap:
NVDIMM-P and CXL Type-3 memory devices.

NVDIMM-P is a JEDEC-standard memory module that combines non-volatile media (like ReRAM or future 3D XPoint alternatives) with DRAM buffers and operates over the native DDR5 interface.

The JEDEC JESD304-4.01 specification defines how NVDIMM-P modules operate on the DDR4/DDR5 interface alongside traditional DRAM.
Read the standard on JEDEC’s official site.

• Plugs directly into standard DDR5 DIMM slots
• Operates over the CPU’s memory bus, not PCIe
• Offers both App-Direct and Memory Mode, similar to Optane DCPMM

• ~120–150 ns latency (very close to DRAM)
• Bandwidth: comparable to DDR5-4800
• Capacity per module: 128 GB to 512 GB expected by late 2025
• Power loss protection via onboard capacitors

• Linux: PMDK, daxctl, ndctl fully support NVDIMM-P out of the box
• Windows Server 2025: DAX support in NTFS and ReFS
• Compatible with existing PMEM-aware apps: SAP HANA, Redis, RocksDB, VMware

• In-memory databases with fast restart requirements
• Write-heavy apps needing persistence (logging, journaling, OLTP)
• Virtualized workloads where DRAM is cost-prohibitive

CXL (Compute Express Link) Type-3 devices enable memory expansion and pooling over PCIe, allowing memory to live outside the CPU socket, attached via a fabric.

• Uses PCIe 5.0 / 6.0 physical lanes
• Enables device memory to be mapped into system address space
• Protocols:
  • CXL.io: control plane (PCIe-compatible)
  • CXL.mem: load/store access to device memory
  • CXL.cache: optional cache coherency for host–device interaction

• ~300–500 ns round-trip latency
• Higher than NVDIMM-P but much lower than SSDs or NVMe-over-Fabrics
• Bandwidth: PCIe-dependent (x8 or x16)

• Enables multi-host memory pooling with CXL switches
• Perfect for disaggregated architectures (e.g., DPUs, composable infrastructure)

• Linux 5.12+ includes CXL core driver
• Tools: cxl-cli, memdev, region, and standard PMEM file systems
• Actively being adopted in hyperscaler and HPC environments

• AI inference or caching workloads that don’t need lowest latency
• Memory expansion in dense edge servers or cloud nodes
• Future-ready setups using fabric-attached memory with DPUs

For more on the CXL memory specification and its roadmap, visit the Compute Express Link Consortium.

Memory Type	Avg. Latency
DDR5 DRAM	~80 ns
NVDIMM-P	~120–150 ns
CXL Type-3	~350–500 ns
NVMe SSD	~80,000 ns

If latency matters (Redis, OLAP, OLTP), go NVDIMM-P.
If you’re optimizing for flexibility and scaling, go CXL.

Constraint	Favor
Limited DDR5 DIMM slots	CXL (uses PCIe lanes)
Limited PCIe lanes	NVDIMM-P (plugs into existing DIMM channels)
Need to scale memory across hosts	CXL with pooling switch
Want to stay socket-local, fast	NVDIMM-P

• NVDIMM-P is simple, socket-local, latency-focused, and excellent for DRAM extension.
• CXL Type-3 is composable, fabric-aware, and built for datacenter-scale flexibility.

Feature / Goal	NVDIMM-P	CXL Type-3
Latency-sensitive (e.g., Redis, HANA restart)	Suitable	Acceptable (higher latency)
Higher memory capacity per host	Yes	Yes
Multi-host memory sharing	No	Yes
Uses DDR5 DIMM slots	Yes	No
Uses PCIe lanes	No	Yes
Easier deployment today	Yes	Requires CXL-capable CPUs & BIOS
Long-term composable infrastructure	Limited	Strong

Persistent memory isn’t just theoretical anymore — it’s in production across enterprise stacks. Here’s how leading teams are using it in the field:

With PMEM configured in App Direct mode, SAP HANA can store columnar in-memory tables persistently.
Result: Database restart time drops from ~15 minutes to under 60 seconds after OS reboot or crash

When Redis is configured for PMDK back-end storage, it gains:

• Persistent key-value state even after crashes
• Lower write amplification
• Faster cold-start loading

vSphere supports PMEM in:

• “vPMEM” mode (exposes PMEM to VMs as virtual NVDIMMs)
• “vPMEMDisk” mode (PMEM-backed datastores)

Used in VDI, SAP, and low-latency enterprise workloads, it cuts VM startup times and increases density.

Data Processing Units (DPUs) paired with CXL switches enable remote memory pooling across hosts.
This allows:

• Composable memory expansion on-demand
• Better DRAM/PMEM utilization per rack
• Clean separation of compute and memory domains

Use case: Edge computing, CDN nodes, or multi-tenant environments with dynamic scaling.This allows:

When inference engines (e.g. TensorRT, ONNX Runtime) are memory-bound, persistent memory provides a mid-latency, high-capacity cache to avoid SSD-bound reads.
This benefits:

• LLM inference with token caching
• Image and speech pipelines needing high batch throughput

Here’s how PMEM compares when factoring latency, endurance, and $/GB — especially for workloads where DRAM alone doesn’t scale:

Memory Tier	Latency	Cost/GB	Endurance	Use Case
DRAM	80 ns	~€8	Very High	Active compute
PMEM	120–500 ns	~€3	Medium (20–60 DWPD)	Tiered memory, fast restart
SSD (NVMe)	80–100 µs	~€0.08	Low	Bulk storage

Total Memory Need: 2 TB

Option 1: 100% DRAM

• Cost = €16,000
• Fast but not scalable

Option 2: 1 TB DRAM + 1 TB PMEM

• Cost = €11,000
• Only ~25% latency hit for cold-tier data
• Restarts are faster; endurance is still enterprise-grade

Result: ~30% cost savings with ~90% performance retention when tiered properly.

The next 36 months will define how persistent memory scales beyond stopgap solutions. Here’s what’s coming—and what it means for data center strategy.

• Next-gen DDR5 module that stacks more ranks using a built-in multiplexer
• Allows twice the capacity per DIMM without increasing pin count
• Enables up to 2 TB per socket without touching PMEM
• First samples expected with Intel Granite Rapids (2026) and AMD Turin (Zen 5 EPYC)

• Combines High Bandwidth Memory with onboard logic (PIM)
• Data is processed directly in-memory, reducing CPU load and data movement
• Ideal for AI inference, real-time analytics, and ultra-low-latency workloads
• Early demos by Samsung, SK Hynix, and UPMEM

• Enables memory pooling and switching across multiple hosts
• Adds multi-level switching, memory sharing, and fine-grained device partitioning
• Supports “memory as a service” in cloud-native environments
• Requires CXL-capable CPUs + memory switch silicon (e.g., Astera, Montage)

• Samsung & Liqid have demoed rack-level memory disaggregation
• Real-world: boot a server with zero local DRAM, fetch memory over CXL
• Fully programmable memory topologies
• Early deployments in hyperscaler labs, telco edge pilots

Developers need to adopt new programming models and tools to fully utilize persistent memory’s benefits. This adds a learning curve and development overhead, especially in environments with legacy systems or limited in-house expertise.

Year	Technology Milestone	Who’s Adopting
2025	NVDIMM-P samples, CXL 2.0 boards	Labs, early edge
2026	Granite Rapids & Turin CPUs, CXL 3.0 fabrics	Tier-1 DCs, telco nodes
2027	MR-DIMM volume, HBM-PIM inference cards	AI, HPC
2028	Rack-scale memory disaggregation	Cloud-native and hyperscalers

In 2025 and beyond, persistent memory is a strategic tool, not just a niche component.
Whether you’re upgrading servers, designing edge infrastructure, or scaling AI inference—DRAM alone won’t cut it.

NVDIMM-P offers the lowest-latency upgrade path.
CXL memory unlocks the future of pooled, fabric-based infrastructure.
Both are here, both are real, and both will reshape memory architectures over the next 36 months.