(MENAFN- EIN Presswire) EINPresswire/ -- "How Large Will The Vector Database For Time‐Series Internet Of Things (IoT) Market Be By 2025?
The scale of the vector database for time‐series internet of things (IoT) market has increased tremendously over recent years. The growth from $1.52 billion in 2024 to an estimated $1.92 billion in 2025, represents a compound annual growth rate (CAGR) of 26.9%. This notable expansion in the past can be linked to the escalating integration of cloud platforms with vector databases, a heightened focus on data security and compliance, increased investments in smart manufacturing and industrial IoT, expanding usage of sensor-rich environments for monitoring purposes, along with growing interest in digital twins for industrial applications.

We anticipate a significant expansion in the vector database for time-series internet of things (IoT) market in the coming years, with its value predicted to reach $4.92 billion by 2029, translating to a compound annual growth rate (CAGR) of 26.5%. This anticipated growth during the forecast period can be credited to increased integration of AI and machine learning in IoT, escalated demands for real-time data analysis, proliferation of connected devices and sensors, growing need for low-latency query processing, and a heightened focus on scalable and superior performance storage solutions. In this forecast period, the key trends to note include enhancements in real-time data analysis, advanced incorporation of machine learning, invention in data compression methods, integration of AI-driven query optimization and advancements in hybrid cloud implementation.

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What Are The Major Driving Forces Influencing The Vector Database For Time‐Series Internet Of Things (IoT) Market Landscape?
The surge in the use of IoT devices is predicted to drive the expansion of the vector database for time-series internet of things (IoT) market. IoT gadgets are physical entities, featuring sensors and internet connectivity, that are capable of collecting, disseminating, and responding to data instantaneously. Their popularity is attributed to their knack to boost efficiency through the automation of processes and providing real-time data insights, enabling quicker and smarter decision-making for businesses and consumers. In terms of time-series IoT, a vector database is handy due to its ability to process and analyze bulk sensor data effectively, equipping IoT devices with the ability to provide swifter, more accurate real-time insights. For instance, Ericsson, a telecommunications company based in Sweden, predicted in September 2024 that broadband and critical IoT (4G/5G) connections are expected to double, totaling 4.3 billion by 2030. Consequently, the rise in the usage of IoT devices is propelling the expansion of the vector database for time-series internet of things (IoT) market.

Who Are The Top Players In The Vector Database For Time‐Series Internet Of Things (IoT) Market?
Major players in the Vector Database For Time‐Series Internet Of Things (IoT) Global Market Report 2025 include:
. Microsoft Corp.
. Alibaba Group Holding Limited
. International Business Machines Corporation
. MongoDB Inc.
. Elastic N.V.
. Redis Ltd.
. Kx Systems Inc.
. SingleStore Inc.
. ClickHouse Inc.
. Timescale Inc.

What Are The Top Trends In The Vector Database For Time‐Series Internet Of Things (IoT) Industry?
The principal players within the vector database for IoT market are concentrating on the development of RAFT-based integration to streamline the execution of consensus algorithms. RAFT-based integration is a consensus tool that guarantees data uniformity and fault-resistance in dispersed systems by coordinating updates amongst various nodes. For example, Zilliz, a firm based in the US that creates and provisions enterprise-level vector databases, unveiled Milvus 2.3 in March 2023. This system employs RAFT-based integration to facilitate heterogeneous computing and uphold efficient coordination in dispersed systems. Thanks to NVIDIA GPU support, it provides improved flexibility and significant enhancements in real-time workload efficiency. It allows for quicker parallel processing and query rates, outperforming Milvus 2.0 by up to four times, and traditional architecture-adapting vector search databases by over ten times. Moreover, its GPU acceleration assures performance that is ten times higher than CPU-exclusive systems, establishing Milvus 2.3 as a robust solution for AI and machine learning workloads.

Market Share And Forecast By Segment In The Global Vector Database For Time‐Series Internet Of Things (IoT) Market
The vector database for time‐series internet of things (iot) market covered in this report is segmented –
1) By Component: Software, Hardware, Services
2) By Deployment Mode: On-Premises, Cloud
3) By Application: Predictive Maintenance, Real-Time Analytics, Asset Tracking, Anomaly Detection, Others Applications
4) By End-User: Manufacturing, Energy And Utilities, Healthcare, Transportation And Logistics, Smart Cities, Others End-Users

Subsegmnets:
1) By Software: Database Management System, Analytics Platform, Data Visualization Tools, Security Software, Integration Middleware
2) By Hardware: Servers, Storage Devices, Edge Devices, Network Equipment, Sensors
3) By Services: Consulting Services, Implementation Services, Maintenance Services, Training Services, Support Services

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Vector Database For Time‐Series Internet Of Things (IoT) Market Regional Insights
In 2024, North America dominated the vector database for time-series internet of things (IoT) market, being the largest region. However, Asia-Pacific is projected to experience the most robust growth during the forecast period. The report encompasses various regions, including Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa.

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