What is NAND flash memory?

The term “NAND” combines “NOT” and “AND,” referring to the logic gate that controls a NAND cell’s internal structure.

Beyond its high-storage density and non-volatility, NAND flash memory stands out for fast data transfer speeds, durability and low power consumption. These characteristics have made NAND flash memory the dominant storage solution for everyday personal electronics—from smartphones to digital cameras, gaming consoles and tablet computers.

On enterprise and industrial levels, examples of NAND usage include data centers, embedded automobile systems, medical imaging equipment and telecommunications infrastructure.

Driven by an increasing demand for data storage across consumer and enterprise applications, the NAND flash memory market size is expected to grow from USD 55.73 billion in 2025 to USD 72.60 billion by 2030. This growth reflects a 5.43% compound annual growth rate (CAGR) during the period.¹ Growth is driven by AI infrastructure investment, increased SSD adoption in consumer electronic devices and 3D chip technology that lowers storage costs.

NAND flash memory is also playing a pivotal role in the adoption of enterprise-level generative AI. Gen AI applications require massive amounts of storage for training data and content, including text, images and videos, which are stored on SSDs powered by NAND flash memory chips.

Unlike volatile memory like DRAM (dynamic random-access memory), which loses data when power is removed, NAND is a non-volatile memory that retains information by trapping electrical charge in its floating gates.

NAND flash memory is relied upon to store data by using special components called floating-gate transistors. These transistors are arranged in a series pattern that functions like a NAND logic gate—a fundamental digital circuit that processes binary signals (ones and zeros) using “NOT” and “AND” operations.

Each memory cell in NAND flash contains two key parts: a control gate and a floating gate, separated by a thin layer of oxide material. Think of it as a tiny container that can trap an electrical charge.

Write operations in NAND cells begin when electrical charge is applied through a process called Fowler-Nordheim tunneling. This charge pushes electrons into the floating gate, where they become trapped, representing a binary value. To erase data, the charge is simply removed from the cell, releasing the trapped electrons.

What makes NAND flash efficient is its block-based architecture. Rather than writing or erasing data one bit at a time, NAND processes information in large blocks. This process makes it ideal for sequential operations and large-scale storage.

NAND flash memory benefits include:

• Non-volatile storage: Can retain data even when power is off, which enables persistent storage for operating systems, applications and user files.

• Low latency: Accelerates data access speeds for high-performance, data-intensive applications.

• High storage density: Packs large storage capacity into compact form factors, from microSD cards to enterprise SSDs.

• Energy efficiency: Needs less power than mechanical drives, which extends battery life and reduces data center costs.

• Durability: More resistant to physical shock and vibration than hard disk drive (HDD) storage devices because it has no moving parts.

• Reliability: Lower failure rates and wear leveling techniques ensure consistent performance, supporting cyber resilience and business continuity.

The foundation for NAND flash memory began with the development of the MOSFET (metal-oxide-semiconductor field-effect transistor) in 1960, which enabled the mass miniaturization of electronics.

In 1967, Dawon Kahng and Simon Min Sze, researchers at Bell Labs, proposed that a MOSFET’s floating gate might be repurposed as reprogrammable read-only memory (ROM).

This concept laid the groundwork for erasable memory technologies. By 1971, Intel engineer Dov Frohman invented erasable programmable read-only memory (EPROM), which used ultraviolet light to erase data through a transparent window on the chip.

The next advancement came with electrically erasable programmable read-only memory (EEPROM) in the late 1970s and early 1980s. Unlike EPROMs, EEPROMs might be erased using electrical signals. This innovation was a significant improvement in convenience and functionality.

Flash memory emerged in the 1980s through the work of Dr. Fujio Masuoka at Toshiba. The term “flash” came from a colleague who observed that data could be erased from the chip “as fast as a camera flash.”

Throughout the 2000s and 2010s, manufacturers made significant strides in NAND flash memory density, performance and reliability through innovations in cell design and manufacturing techniques. These innovations transformed NAND flash from a niche storage technology into the foundation of modern data storage.

There are two types of flash memory: NOR flash and NAND flash.

NAND flash uses “NOT AND” Boolean logic gates with memory cells arranged in series, prioritizing storage density and sequential operations for high-capacity storage needs.

NOR flash uses “NOT OR” Boolean logic gates with flash memory cells connected in parallel, allowing individual bytes to be read and programmed quickly. This process makes NOR flash well suited for applications that require running code directly from memory, such as firmware, BIOS chips and embedded systems. However, NOR flash has slower write and erase speeds, lower storage density and higher costs per bit.

While NOR flash remains important for code execution tasks, NAND flash has become the primary storage technology for most applications. 

NAND flash memory types are classified by the number of bits individual cells can store. Each type has different endurance ratings measured in P/E cycles (program or erase cycles).

They include:

• SLC (single-level cell): SLC, or single-level cells, store one bit per cell. While SLC NAND is the most expensive per gigabyte, it delivers the highest performance, reliability and endurance, with up to 100,000 erase cycles. It is used in enterprise settings that run mission-critical enterprise workloads.

• MLC (multi-level cell): MLC, or multi-level cells, store two bits per cell. It doubles the storage density of SLC while reducing the cost per gigabyte, but it is slower. Offering midrange affordability, MLC is embedded in many consumer SSDs or professional workstations where endurance is less critical.

• TLC (triple-level cell): TLC, or triple-level cells, store three bits per cell. TLC offers lower endurance than SLC and MLC because it has only 3,000 P/E cycles. However, it provides a higher density for storing data at a lower cost and is frequently used in mainstream consumer SSD products. 

• QLC (quad-level cell): QLC, or quad-level cells, store four bits per cell. This specification maximizes storage capacity and minimizes cost per gigabyte, making it optimal for read-intensive workloads (for example, streaming, archiving, large file storage) where write cycle endurance is less critical. QLC also relies heavily on advanced error correction to preserve data integrity.

SLC, or single-level cells, store one bit per cell. While SLC NAND is the most expensive per gigabyte, it delivers the highest performance, reliability and endurance, with up to 100,000 erase cycles. It is used in enterprise settings that run mission-critical enterprise workloads.

Modern SSDs use 3D NAND memory, a type of architecture that stacks multiple layers of memory cells vertically on silicon wafers. Compared to older 2D NAND, which arranges memory cells in a flat matrix, 3D NAND enables a greater number of memory cells within the same footprint. This capability optimizes data storage density, capacity and the overall cost per bit of data, allowing for more memory cells.

In a report from S&S Insider, the 3D NAND flash memory market size was valued at USD 17.59 billion in 2023. It is also expected to reach USD 75.44 billion by 2032, growing at a CAGR of 17.61% from 2024–2032.²

3D NAND technology plays a crucial role in storing data in the artificial intelligence (AI) era. With write speeds that are up to 50% faster than traditional NAND solutions, 3D NAND-powered SSDs and all-flash arrays are being used as storage for gen AI. This supports fast access to pre-trained models and large datasets near processing units. By reducing data retrieval latency, 3D NAND improves the performance of AI and machine learning (ML) workflows.