Company patents
NetApp, Inc.
Net App, Inc. demonstrates a strong and sustained focus on core data management technologies, with Input/Output & User Interfaces (41.9% of portfolio) and System Reliability & Diagnostics (37.6% of portfolio) being dominant areas. While Databases & Information Retrieval saw a significant 34.4% YoY growth in 2024, it surprisingly experienced a decline in 2025, and patenting activity across most categories, including this one, shows a sharp decrease so far in 2026, which is partial data.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
1,083 US filings (since 2023) · 12 categories · 35 themes
Encompasses strategies and technologies to ensure the availability, integrity, and recoverability of data and systems, including robust backup, replication, error correction, and efficient data restoration.
Techniques for distributing computational tasks, data storage, and service logic across cloud data centers, edge devices, and user equipment to improve performance, resilience, or resource utilization. This includes architectures for split rendering, decentralized ledgers, and microservices.
Hardware and control techniques for optimizing memory access latency, ensuring data integrity, and managing storage resources efficiently. This includes error correction, read/write voltage control, and intelligent data placement or in-memory computation.
Mechanisms to facilitate the secure exchange of data between different entities or systems while enforcing usage policies, managing digital content rights, and ensuring data consistency during replication or transfer.
Systems and methods for collecting, processing, and ensuring the quality and consistency of data used for network monitoring, asset management, and operational decision-making, including conflict detection and reliability scoring.
Methods and systems for efficiently allocating computing resources, balancing workloads, and managing power states to improve performance, reduce energy consumption, or enhance reliability in computing platforms.
Techniques for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.
Techniques and systems designed to monitor network health, diagnose issues, optimize traffic flow, and ensure continuous operation and reduced downtime in complex network environments, including cloud and storage area networks.
Systems and methods for automatically deploying, configuring, and updating network devices and services, including software updates, client onboarding, and topology management across various network types.
Technologies enabling the creation and management of virtual computing environments, including virtual machines and virtual desktops, with an emphasis on secure and efficient remote access, updates, and performance.
Techniques and systems for optimizing network traffic flow, distributing loads across multiple paths or resources, and ensuring quality of service based on various criteria like application type, latency, or resource availability. This includes dynamic path selection, congestion control, and resource allocation.
Technologies for deploying, managing, and governing applications and services in cloud environments, particularly focusing on containerization, microservice architectures, API gateways, and distributed data management.
Managing and optimizing network resources and services deployed at the edge of the network or within cloud environments, including distributed domain name resolution, resource exposure analysis, and traffic management specific to distributed architectures.
Tools and processes for assessing, monitoring, and improving the security configuration and external accessibility of resources deployed within cloud computing environments.
Techniques for monitoring system components and behaviors to anticipate failures, performance degradation, or anomalies, often leveraging machine learning for pattern recognition and forecasting.
Methods and systems for integrating, transforming, and managing complex or domain-specific data from disparate sources into a unified structure, often for specific applications like social networks, genomics, or business forms.
Involves systems designed to automatically detect errors or failures and initiate predefined or intelligent corrective actions, recovery procedures, or notifications to minimize downtime and manual intervention.
Systems and methods for authenticating users, devices, or applications, authorizing their access to resources based on policies, and managing digital identities across various platforms.
Methods and frameworks for systematically verifying the correctness, performance, and security of software systems, including infrastructure as code, virtual workloads, APIs, and identifying potential vulnerabilities or inconsistencies.
Applying artificial intelligence and machine learning techniques to enhance cryptographic systems, such as generating encryption models, improving zero-trust architectures, or enabling privacy-preserving computations like federated learning.
Systems and methods for securely and reliably delivering, installing, and managing software or firmware updates to distributed or embedded devices, often considering network conditions, resource constraints, or storage repartitioning.
Technologies for establishing and managing high-bandwidth, low-latency communication pathways between computing components, peripherals, or systems, focusing on signal integrity, synchronization, and interface standards.
Systems and methods for identifying and blocking unauthorized access, malicious activities, or abnormal behavior within a network by analyzing traffic, system logs, or behavioral patterns.
Utilizing specialized hardware components such as network processing units (NPUs) or dedicated acceleration circuits to offload and speed up network packet processing, traffic generation, or time-sensitive network operations.
Systems that process data to provide personalized recommendations, predict events, or automate decision-making processes based on learned patterns, user behavior, or environmental factors.
Technologies that process, analyze, and leverage geographic information system (GIS) data, location data, and spatial analytics for applications such as monitoring, navigation, and environmental assessment.
Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.
Systems and methods utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.
Systems and methods for automating multi-step tasks, business processes, or service interactions, often involving AI agents, programmable interfaces, or formal orchestration languages to streamline operations.
Technologies for establishing and maintaining secure communication channels between devices or networks, often employing encryption, secure protocols, or virtual private networks (VPNs).
Techniques for rendering, interacting with, and managing content within augmented or virtual reality environments, including spatial tracking, gaze interaction, and dynamic multi-application display management.
Platforms and methods for aggregating data from diverse sources, generating dynamic content, and delivering it efficiently to users, often involving social media, programmatic advertising, or interactive experiences within cloud environments.
Methods and systems for displaying complex data in three-dimensional graphical formats, allowing users to manipulate, explore, and derive insights from the data through interactive controls.
Methods and systems for monitoring, controlling, and managing Internet of Things (IoT) devices and their communication networks, often involving adaptive or intelligent frameworks for data acquisition, relay, and automation.
Methods for training machine learning models across multiple decentralized devices or servers while keeping data localized, often involving aggregation of model parameters and secure communication.
Patents
Showing 1-10 of 389
Memory System Performance & Reliability