¼¼°èÀÇ Å¬·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î ½ÃÀå ±Ô¸ð, Á¡À¯À², µ¿Ç⠺м® º¸°í¼­ : À¯Çüº°, Àü°³ Çüź°, ±â¾÷ ±Ô¸ðº°, ÃÖÁ¾ ¿ëµµº°, Áö¿ªº°, ºÎ¹®º° ¿¹Ãø(2025-2030³â)
Clustering Software Market Size, Share & Trends Analysis Report By Type (Self-Service Clustering, Managed Clustering, Hybrid Clustering), By Deployment, By Enterprise Size, By End-use, By Region, And Segment Forecasts, 2025 - 2030
»óǰÄÚµå : 1751495
¸®¼­Ä¡»ç : Grand View Research, Inc.
¹ßÇàÀÏ : 2025³â 05¿ù
ÆäÀÌÁö Á¤º¸ : ¿µ¹® 120 Pages
 ¶óÀ̼±½º & °¡°Ý (ºÎ°¡¼¼ º°µµ)
US $ 4,950 £Ü 6,936,000
Unprintable PDF & Excel (Single User License) help
º¸°í¼­ PDF ¹× ¿¢¼¿À» 1Àθ¸ »ç¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ® µîÀÇ º¹»ç ¹× ºÙ¿©³Ö±â, Àμâ´Â ºÒ°¡´ÉÇÕ´Ï´Ù.
US $ 5,950 £Ü 8,338,000
Printable PDF & Excel (5-User License) help
º¸°í¼­ PDF ¹× ¿¢¼¿À» µ¿ÀÏ ±â¾÷ ³» µ¿ÀÏ ºÎ¼­¿¡¼­ ÃÖ´ë 5¸í±îÁö »ç¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ® µîÀÇ º¹»ç ¹× ºÙ¿©³Ö±â, Àμâ´Â °¡´ÉÇÕ´Ï´Ù.
US $ 7,950 £Ü 11,141,000
Printable PDF & Excel (Enterprise License) help
º¸°í¼­ ±¸¸Å ±â¾÷ ¹× ±× ÀÚȸ»ç, °ü°è»ç°¡ »ç¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀ̸ç, PDF ¹× ¿¢¼¿ ÅØ½ºÆ® µîÀÇ º¹»ç ¹× ºÙ¿©³Ö±â, ÀμⰡ °¡´ÉÇÕ´Ï´Ù.


¤± Add-on °¡´É: °í°´ÀÇ ¿äû¿¡ µû¶ó ÀÏÁ¤ÇÑ ¹üÀ§ ³»¿¡¼­ CustomizationÀÌ °¡´ÉÇÕ´Ï´Ù. ÀÚ¼¼ÇÑ »çÇ×Àº ¹®ÀÇÇØ Áֽñ⠹ٶø´Ï´Ù.

Çѱ۸ñÂ÷

Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î ½ÃÀå ±Ô¸ð ¹× µ¿Çâ

¼¼°è Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î ½ÃÀå ±Ô¸ð´Â 2024³â 51¾ï 9,000¸¸ ´Þ·¯·Î ÃßÁ¤µÇ¸ç, 2025-2030³â ¿¬Æò±Õ 11.4%ÀÇ ¼ºÀå·üÀ» º¸ÀÏ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. »ê¾÷ Àü¹Ý¿¡ °ÉÃÄ »ý¼ºµÇ´Â µ¥ÀÌÅÍÀÇ ¾çÀÌ Áõ°¡Çϰí ÀÖ´Â °ÍÀÌ Å¬·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î ½ÃÀåÀ» ÃËÁøÇÏ´Â ÁÖ¿ä ¿äÀÎÀÔ´Ï´Ù. Ä¿³ØÆ¼µå µð¹ÙÀ̽º, IoT ³×Æ®¿öÅ©, ¼Ò¼È ¹Ìµð¾î Ç÷§Æû, ÀüÀÚ»ó°Å·¡ Ȱµ¿ÀÇ È®»êÀ¸·Î Á¶Á÷Àº ¸ÅÀÏ ´ë·®ÀÇ Á¤Çü ¹× ºñÁ¤Çü µ¥ÀÌÅ͸¦ »ý¼ºÇϰí ÀÖ½À´Ï´Ù. ÀÌ ¹æ´ëÇÑ µ¥ÀÌÅ͸¦ °ü¸®Çϰí ÀλçÀÌÆ®·ÂÀ» µµÃâÇÏ´Â °ÍÀº ºñÁî´Ï½º ¼º°ø¿¡ ÀÖ¾î ´õ¿í º¹ÀâÇϰí Áß¿äÇØÁö°í ÀÖ½À´Ï´Ù. Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î´Â ±â¾÷ÀÌ ´ë±Ô¸ð µ¥ÀÌÅÍ ¼¼Æ®¸¦ ÀÇ¹Ì ÀÖ´Â Ä«Å×°í¸®·Î ±×·ìÈ­ÇÏ¿© ´õ ³ªÀº ºÐ¼®, ÀÇ»ç°áÁ¤ ¹× Àü·« ¼ö¸³À» ÇÒ ¼ö ÀÖµµ·Ï µµ¿ÍÁÝ´Ï´Ù.

±â¾÷µéÀÌ ºòµ¥ÀÌÅ͸¦ Ȱ¿ëÇÏ¿© °æÀï ¿ìÀ§¸¦ È®º¸Çϱâ À§ÇØ ³ë·ÂÇÏ´Â °¡¿îµ¥, ÆÐÅÏÀ» ÀÚµ¿À¸·Î °¨ÁöÇϰí, ½ÃÀåÀ» ¼¼ºÐÈ­Çϰí, ¿î¿µÀ» ÃÖÀûÈ­ÇÒ ¼ö ÀÖ´Â °í±Þ Ŭ·¯½ºÅ͸µ ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä°¡ ºü¸£°Ô Áõ°¡Çϸ鼭 ½ÃÀåÀ» ÁÖµµÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, »çÀ̹ö º¸¾È ºÐ¾ß¿¡¼­ Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾îÀÇ È°¿ëÀÌ È®´ëµÇ°í ÀÖ´Â °Íµµ Áß¿äÇÑ ¼ºÀå µ¿·ÂÀÌ µÇ°í ÀÖ½À´Ï´Ù. »çÀ̹ö À§ÇùÀÌ °íµµÈ­µÊ¿¡ µû¶ó ±âÁ¸ º¸¾È ½Ã½ºÅÛÀ¸·Î´Â ÀÌ»ó ¡Èijª APT(Advanced Persistent Threat)¸¦ °¨ÁöÇÏÁö ¸øÇÏ´Â °æ¿ì°¡ ¸¹¾ÆÁö°í ÀÖ½À´Ï´Ù. Ŭ·¯½ºÅ͸µ ±â¼úÀ» ÅëÇØ »çÀ̹ö º¸¾ÈÆÀÀº ºñÁ¤»óÀûÀÎ ÆÐÅÏÀ» ½Äº°Çϰí, ¾ÇÀÇÀûÀΠȰµ¿À» ¼¼ºÐÈ­Çϸç, »ç¶÷ÀÇ ¸íÈ®ÇÑ ¶óº§¸µ ¾øÀ̵µ Á߿䵵¿¡ µû¶ó À§ÇùÀÇ ¿ì¼±¼øÀ§¸¦ Á¤ÇÒ ¼ö ÀÖ½À´Ï´Ù. µ¥ÀÌÅÍ À¯Ãâ, ·£¼¶¿þ¾î °ø°Ý, ±âŸ »çÀ̹ö ¹üÁËÀÇ ¹ß»ýÀÌ Áõ°¡ÇÔ¿¡ µû¶ó Àü ¼¼°è Á¶Á÷µéÀº Ŭ·¯½ºÅ͸µ ¾Ë°í¸®ÁòÀ» Ȱ¿ëÇÏ¿© À§Çù °¨Áö ¹× ´ëÀÀ ´É·ÂÀ» °­È­ÇÏ´Â º¸¾È ¼Ö·ç¼Ç¿¡ ¸¹Àº ÅõÀÚ¸¦ Çϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ´Éµ¿ÀûÀ̰í Áö´ÉÀûÀÎ »çÀ̹ö º¸¾È ´ëÃ¥¿¡ ´ëÇÑ °ü½ÉÀº Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î º¥´õµé¿¡°Ô Å« ºñÁî´Ï½º ±âȸ·Î ÀÛ¿ëÇϰí ÀÖ½À´Ï´Ù.

¶ÇÇÑ, Ŭ¶ó¿ìµå ±â¹Ý Ŭ·¯½ºÅ͸µ ¼Ö·ç¼ÇÀÇ µîÀåÀ¸·Î Á¢±Ù¼º°ú È®À强ÀÌ °£¼ÒÈ­µÇ¾î º¸´Ù ±¤¹üÀ§ÇÑ ½ÃÀå µµÀÔÀ» ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ±âÁ¸ On-PremiseÇü Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î´Â Çϵå¿þ¾î¿Í ¼÷·ÃµÈ IT Àη¿¡ ´ëÇÑ ¸·´ëÇÑ ¼±ÅõÀÚ°¡ ÇÊ¿äÇÑ °æ¿ì°¡ ¸¹½À´Ï´Ù. ¹Ý¸é, Ŭ¶ó¿ìµå ±â¹Ý Ŭ·¯½ºÅ͸µ Ç÷§ÆûÀº È®À强, À¯¿¬¼º, ºñ¿ë È¿À²¼ºÀÌ ¶Ù¾î³ª ¸ðµç ±Ô¸ðÀÇ ±â¾÷ÀÌ º¹ÀâÇÑ ÀÎÇÁ¶ó¸¦ À¯ÁöÇØ¾ß ÇÏ´Â ºÎ´ã ¾øÀÌ °í±Þ Ŭ·¯½ºÅ͸µ ±â´ÉÀÇ ÇýÅÃÀ» ´©¸± ¼ö ÀÖ½À´Ï´Ù. µðÁöÅÐ ÀüȯÀ» ¼ö¿ëÇϰí Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê ¾ÆÅ°ÅØÃ³·Î ÀüȯÇÏ´Â ±â¾÷ÀÌ ´Ã¾î³²¿¡ µû¶ó, µµÀÔÀÌ ¿ëÀÌÇÑ ±¸µ¶ ±â¹Ý Ŭ·¯½ºÅ͸µ ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä°¡ ±ÞÁõÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, Ŭ¶ó¿ìµå ¹èÆ÷ ¸ðµ¨Àº Áö¸®ÀûÀ¸·Î ºÐ»êµÈ ÆÀ °£ÀÇ ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸® ¹× Çù¾÷À» ¿ëÀÌÇÏ°Ô Çϱ⠶§¹®¿¡ Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î´Â ÃֽŠÁ¶Á÷¿¡ ´õ¿í ¸Å·ÂÀûÀ¸·Î ´Ù°¡¿À°í ÀÖ½À´Ï´Ù.

¶ÇÇÑ, ½º¸¶Æ®½ÃƼ¿Í IoT µð¹ÙÀ̽ºÀÇ È®»êÀº Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î ½ÃÀåÀÇ ¼ºÀåÀ» °¡¼ÓÇϰí ÀÖÀ¸¸ç, IoT ¼¾¼­ÀÇ ½Ç½Ã°£ µ¥ÀÌÅÍ¿¡ Å©°Ô ÀÇÁ¸ÇÏ´Â ½º¸¶Æ®½ÃƼ ±¸»óÀº ¹æ´ëÇÏ°í ´Ù¾çÇÑ µ¥ÀÌÅÍ ½ºÆ®¸²À» ó¸®Çϰí Àǹ̸¦ ºÎ¿©ÇÒ ¼ö ÀÖ´Â °í±Þ ºÐ¼® µµ±¸°¡ ÇÊ¿äÇÕ´Ï´Ù. ÇÊ¿äÇÕ´Ï´Ù. Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î´Â ½º¸¶Æ® ±³Åë ½Ã½ºÅÛ, ¿¡³ÊÁö ±×¸®µå, Æó±â¹° °ü¸® ¼Ö·ç¼Ç, °ø°ø ¾ÈÀü ½Ã½ºÅÛ¿¡¼­ ¼öÁýµÈ µ¥ÀÌÅ͸¦ Á¤¸®ÇÏ´Â µ¥ Áß¿äÇÑ ¿ªÇÒÀ» ÇÕ´Ï´Ù. À̸¦ ÅëÇØ µµ½Ã °èȹÀÚ¿Í °ü¸®ÀÚ´Â Æ®·»µå¸¦ ÆÄ¾ÇÇϰí, ¼­ºñ½º¸¦ ÃÖÀûÈ­Çϰí, ¹®Á¦¿¡ ´Éµ¿ÀûÀ¸·Î ´ëÀÀÇÒ ¼ö ÀÖ½À´Ï´Ù. °¢±¹ Á¤ºÎ°¡ ½º¸¶Æ® ÀÎÇÁ¶ó¿¡ ´ëÇÑ ÅõÀÚ¸¦ ´Ã¸®¸é¼­ IoT »ýÅÂ°è °ü¸®, ºÐ¼® ¹× ÀλçÀÌÆ®·Â µµÃâÀ» À§ÇÑ Å¬·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾îÀÇ »ç¿ë ±âȸ´Â Å©°Ô È®´ëµÉ °ÍÀ¸·Î º¸ÀÔ´Ï´Ù.

¸ñÂ÷

Á¦1Àå Á¶»ç ¹æ¹ý°ú ¹üÀ§

Á¦2Àå ÁÖ¿ä ¿ä¾à

Á¦3Àå Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î º¯¼ö, µ¿Çâ, ¹üÀ§

Á¦4Àå Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î : À¯Çüº°, ÃßÁ¤, µ¿Ç⠺м®

Á¦5Àå Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î : Àü°³ Çüź°, ÃßÁ¤, µ¿Ç⠺м®

Á¦6Àå Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î : ±â¾÷ ±Ô¸ðº°, ÃßÁ¤, µ¿Ç⠺м®

Á¦7Àå Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î : ÃÖÁ¾ ¿ëµµº°, ÃßÁ¤, µ¿Ç⠺м®

Á¦8Àå Ŭ·¯½ºÅ͸µ ¼ÒÇÁÆ®¿þ¾î ½ÃÀå : Áö¿ªº°, ÃßÁ¤, µ¿Ç⠺м®

Á¦9Àå °æÀï ±¸µµ

LSH
¿µ¹® ¸ñÂ÷

¿µ¹®¸ñÂ÷

Clustering Software Market Size & Trends:

The global clustering software market size was estimated at USD 5.19 billion in 2024 and is anticipated to grow at a CAGR of 11.4% from 2025 to 2030. The increasing volume of data generated across industries is a major driver fueling the clustering software market. Organizations produce massive amounts of structured and unstructured data daily with the proliferation of connected devices, IoT networks, social media platforms, and e-commerce activities. Managing and extracting insights from this vast data is becoming more complex and crucial for business success. Clustering software helps businesses to group large datasets into meaningful categories, enabling better analysis, decision-making, and strategy formulation.

As companies strive to leverage big data to gain competitive advantages, the need for sophisticated clustering solutions that can automatically detect patterns, segment markets, and optimize operations is rapidly increasing, thus propelling the market forward. The expanding applications of clustering software in cybersecurity also act as a critical growth driver. As cyber threats become more sophisticated, traditional security systems often do not detect anomalies or advanced persistent threats (APTs). Clustering techniques allow cybersecurity teams to identify unusual patterns, segment malicious activities, and prioritize threats based on severity without explicit human labeling. With the growing incidence of data breaches, ransomware attacks, and other cybercrimes, organizations across the globe are investing heavily in security solutions that leverage clustering algorithms to enhance threat detection and response capabilities. This focus on proactive and intelligent cybersecurity measures creates robust opportunities for clustering software vendors.

Moreover, the emergence of cloud-based clustering solutions simplifies access and scalability, thus driving broader market adoption. Traditional on-premises clustering software often requires significant upfront investment in hardware and skilled IT staff. In contrast, cloud-based clustering platforms offer scalability, flexibility, and cost-effectiveness, allowing businesses of all sizes to benefit from advanced clustering capabilities without the burden of maintaining complex infrastructure. As more enterprises embrace digital transformation and shift toward cloud-native architectures, the demand for easy-to-deploy, subscription-based clustering solutions is rising sharply. Cloud deployment models also facilitate real-time data processing and collaboration across geographically dispersed teams, making clustering software even more attractive to modern organizations.

Furthermore, the proliferation of smart cities and IoT devices is driving the growth of the clustering software market. Smart city initiatives, which rely heavily on real-time data from IoT sensors, require sophisticated analytics tools to process and make sense of vast and diverse data streams. Clustering software is key in organizing data collected from smart traffic systems, energy grids, waste management solutions, and public safety systems. It enables urban planners and administrators to identify trends, optimize services, and proactively respond to issues. With governments worldwide increasingly investing in smart infrastructure, the use of clustering software to manage, analyze, and derive insights from IoT ecosystems is set to expand significantly.

Global Clustering Software Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the global clustering software market report based on type, deployment, enterprise size, end use, and region:

Table of Contents

Chapter 1. Methodology and Scope

Chapter 2. Executive Summary

Chapter 3. Clustering Software Variables, Trends, & Scope

Chapter 4. Clustering Software: Type Estimates & Trend Analysis

Chapter 5. Clustering Software: Deployment Estimates & Trend Analysis

Chapter 6. Clustering Software: Enterprise Size Estimates & Trend Analysis

Chapter 7. Clustering Software: End Use Estimates & Trend Analysis

Chapter 8. Clustering Software Market: Regional Estimates & Trend Analysis

Chapter 9. Competitive Landscape

(ÁÖ)±Û·Î¹úÀÎÆ÷¸ÞÀÌ¼Ç 02-2025-2992 kr-info@giikorea.co.kr
¨Ï Copyright Global Information, Inc. All rights reserved.
PC¹öÀü º¸±â