¼¼°èÀÇ º¤ÅÍ µ¥ÀÌÅͺ£À̽º ½ÃÀå ±Ô¸ð, Á¡À¯À² ¹× »ê¾÷ µ¿Ç⠺м® º¸°í¼­ : Á¦°ø Á¦Ç°º°, ±â¼úº°, »ê¾÷º° ¹× Áö¿ªº° Àü¸Á ¹× ¿¹Ãø(2023-2030³â)
Global Vector Database Market Size, Share & Industry Trends Analysis Report By Offering, By Technology (Natural Language Processing, Computer Vision, and Recommendation Systems), By Vertical, By Regional Outlook and Forecast, 2023 - 2030
»óǰÄÚµå : 1395858
¸®¼­Ä¡»ç : KBV Research
¹ßÇàÀÏ : 2023³â 11¿ù
ÆäÀÌÁö Á¤º¸ : ¿µ¹® 250 Pages
 ¶óÀ̼±½º & °¡°Ý (ºÎ°¡¼¼ º°µµ)
US $ 3,600 £Ü 4,921,000
PDF (Single User License) help
PDF º¸°í¼­¸¦ 1¸í¸¸ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ®ÀÇ Copy & Paste °¡´ÉÇÕ´Ï´Ù. Àμ⠰¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.
US $ 4,320 £Ü 5,905,000
PDF (Multi User License) help
PDF º¸°í¼­¸¦ µ¿ÀÏ ±â¾÷ÀÇ 10¸í±îÁö ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ®ÀÇ Copy & Paste °¡´ÉÇÕ´Ï´Ù. Àμ⠰¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.
US $ 6,048 £Ü 8,268,000
PDF (Corporate User License) help
PDF º¸°í¼­¸¦ µ¿ÀÏ ±â¾÷ÀÇ ¸ðµç ºÐÀÌ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ®ÀÇ Copy & Paste °¡´ÉÇÕ´Ï´Ù. Àμ⠰¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.


Çѱ۸ñÂ÷

º¤ÅÍ µ¥ÀÌÅͺ£À̽º ½ÃÀå ±Ô¸ð´Â 2030³â±îÁö 64¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹»óµÇ¸ç, ¿¹Ãø ±â°£ µ¿¾È ¿¬Æò±Õ º¹ÇÕ ¼ºÀå·ü(CAGR)Àº 22.3%¸¦ ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

±×·¯³ª °í¼º´É ¼­¹ö, ´ë¿ë·® ¸Þ¸ð¸®, ƯÁ¤ ó¸® ÀåÄ¡(°è»ê ¼Óµµ¸¦ ³ôÀÌ´Â GPU µî) µî ÇÊ¿äÇÑ ÀÎÇÁ¶ó¸¦ °®Ãß±â À§Çؼ­´Â ¸¹Àº Ãʱ⠺ñ¿ëÀÌ ¼Ò¿äµË´Ï´Ù. ¿¹¸¦ µé¾î, Àθ޸𸮠µ¥ÀÌÅͺ£À̽º´Â µ¥ÀÌÅ͸¦ ¸Þ¸ð¸®¿¡ Á÷Á¢ ÀúÀåÇϰí ó¸®Çϱ⠶§¹®¿¡ ÃæºÐÇÑ ¸Þ¸ð¸® ¿ë·®À» °®Ãá °ß°íÇÑ ÀÎÇÁ¶ó°¡ ÇÊ¿äÇÕ´Ï´Ù. ÀÌ·¯ÇÑ Æ¯¼öÇÑ Çϵå¿þ¾î ¿ä±¸»çÇ×Àº Ãʱ⠼³Á¤ ºñ¿ëÀ» Å©°Ô Áõ°¡½Ãų ¼ö ÀÖ½À´Ï´Ù. ƯÈ÷ ÅõÀÚ¼öÀÍ·ü(ROI)À̳ª µ¥ÀÌÅͺ£À̽º°¡ Á¶Á÷¿¡ Á¦°øÇÒ ¼ö ÀÖ´Â Á÷Á¢ÀûÀÎ °¡Ä¡¸¦ Æò°¡ÇÒ ¶§ ÀÌ·¯ÇÑ ³ôÀº ºñ¿ëÀº ÁÖÀúÇÏ°Ô ¸¸µå´Â ¿äÀÎÀÌ µÉ ¼ö ÀÖ½À´Ï´Ù. µû¶ó¼­ ÀÌ·¯ÇÑ Ãø¸éÀÌ ÇâÈÄ ¸î ³âµ¿¾È ½ÃÀå ¼ºÀåÀ» ¾ïÁ¦ÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

Á¦°ø Àü¸Á

½ÃÀå ¼¼ºÐÈ­¿¡¼­ ½ÃÀåÀº ¼Ö·ç¼Ç°ú ¼­ºñ½º·Î ±¸ºÐµÇ¸ç, 2022³â ½ÃÀå¿¡¼­´Â ¼Ö·ç¼Ç ºÎ¹®ÀÌ °¡Àå ³ôÀº ¸ÅÃâ Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ¼Ö·ç¼Ç ºÎ¹®Àº »ê¾÷ Àü¹Ý¿¡ °ÉÄ£ ¹æ´ëÇÑ ÀÌ¿ë »ç·Ê·Î ÀÎÇØ Å©°Ô ¼ºÀåÇϰí ÀÖ½À´Ï´Ù. Á¶Á÷ÀÌ ´ë±Ô¸ðÀÇ º¹ÀâÇÑ µ¥ÀÌÅÍ ¼¼Æ®¸¦ ´Ù·ç¸é¼­ È¿À²ÀûÀÎ µ¥ÀÌÅÍ °ü¸® ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä°¡ ±ÞÁõÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ µ¥ÀÌÅͺ£À̽º´Â ¸Ó½Å·¯´×°ú AI¿¡¼­ ÁöÇü °ø°£ µ¥ÀÌÅÍ ºÐ¼®, ½Ã°è¿­ µ¥ÀÌÅÍ Ã³¸®, ±×·¡ÇÁ µ¥ÀÌÅÍ °ü¸® µî ´Ù¾çÇÑ ¿ëµµ¸¦ À§ÇÑ ¼Ö·ç¼ÇÀ» Á¦°øÇÕ´Ï´Ù. ÀÌ·¯ÇÑ µ¥ÀÌÅͺ£À̽º´Â ´Ù¾çÇÑ ÀÌ¿ë »ç·Ê¿¡ ÀûÀÀÇÒ ¼ö Àֱ⠶§¹®¿¡ ¼Ö·ç¼Ç ºÎ¹® ³» ¼ºÀåÀ» °¡¼ÓÇϰí ÀÖ½À´Ï´Ù. ÀÌ¿¡ µû¶ó ÀÌ ºÐ¾ß´Â ÇâÈÄ ¼ºÀå¼¼¸¦ º¸ÀÏ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

±â¼ú Àü¸Á

±â¼úº°·Î º¸¸é, ½ÃÀåÀº ÀÚ¿¬¾î ó¸®, ÄÄÇ»ÅÍ ºñÀü, Ãßõ ½Ã½ºÅÛÀ¸·Î ³ª´µ¸ç, 2022³â¿¡´Â ÄÄÇ»ÅÍ ºñÀü ºÐ¾ß°¡ ½ÃÀå¿¡¼­ °¡Àå Å« ¸ÅÃâ Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ½º¸¶Æ®Æù, °¨½Ã Ä«¸Þ¶ó, »ç¹°ÀÎÅͳÝ(IoT) ±â±â µîÀÇ º¸±ÞÀ¸·Î À̹ÌÁö ¹× ¿µ»ó µ¥ÀÌÅͰ¡ ±ÞÁõÇϸ鼭 µ¥ÀÌÅÍ ¾çÀÌ ±ÞÁõÇϰí ÀÖ½À´Ï´Ù. ÄÄÇ»ÅÍ ºñÀü ¿ëµµ´Â È¿À²ÀûÀÎ ÀúÀå, °Ë»ö, ºÐ¼®ÀÌ ÇÊ¿äÇÑ ¹æ´ëÇÑ ¾çÀÇ ½Ã°¢ µ¥ÀÌÅ͸¦ »ý¼ºÇϴµ¥, º¤ÅÍ µ¥ÀÌÅͺ£À̽º´Â °íÂ÷¿ø µ¥ÀÌÅ͸¦ È¿À²ÀûÀ¸·Î ó¸®ÇÒ ¼ö Àֱ⠶§¹®¿¡ À̸¦ °ü¸®Çϱ⿡ ÀûÇÕÇÕ´Ï´Ù. µû¶ó¼­ ÀÌ ºÐ¾ß´Â ÇâÈÄ ¸î³â¾È¿¡ ±Þ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

»ê¾÷º° Àü¸Á

»ê¾÷º°·Î´Â BFSI, ¼Ò¸Å ¹× ÀüÀÚ»ó°Å·¡, ÇコÄɾî, IT ¹× ITeS, ¹Ìµð¾î ¹× ¿£ÅÍÅ×ÀÎ¸ÕÆ®, Á¦Á¶, ±âŸ·Î ºÐ·ùµÇ¸ç, BFSI ºÎ¹®Àº 2022³â ½ÃÀå¿¡¼­ »ó´çÇÑ ¸ÅÃâ Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµÇ¸ç, BFSI Á¶Á÷Àº ¹æ´ëÇÑ ¾çÀÇ °Å·¡ ¹× °í°´ µ¥ÀÌÅ͸¦ ó¸®Çϰí ÀÖ½À´Ï´Ù. ó¸®Çϰí ÀÖ½À´Ï´Ù. º¤ÅÍ µ¥ÀÌÅͺ£À̽º¸¦ »ç¿ëÇϸé ÀÌ µ¥ÀÌÅ͸¦ ½Ç½Ã°£À¸·Î ºÐ¼®ÇÏ¿© °í°´ Çൿ, À§Çè Æò°¡ ¹× »ç±â ŽÁö¿¡ ´ëÇÑ ÅëÂû·ÂÀ» ¾òÀ» ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ µ¥ÀÌÅͺ£À̽º¸¦ ÅëÇØ ±ÝÀ¶±â°üÀº ÆÐÅϰú Ãß¼¼¸¦ ½Å¼ÓÇÏ°Ô ÆÄ¾ÇÇÏ¿© °³ÀÎÈ­µÈ ¼­ºñ½º¿Í º¸´Ù Á¤È®ÇÑ À§Çè Æò°¡¸¦ °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù.BFSI ºÐ¾ß´Â ½Ã°è¿­, º¹ÀâÇÑ ±ÝÀ¶ ¸ðµ¨, °ü°èÇü µ¥ÀÌÅÍ µî º¹ÀâÇÑ µ¥ÀÌÅÍ ±¸Á¶¸¦ ´Ù·ç°í ÀÖ½À´Ï´Ù. µû¶ó¼­ ÀÌ ºÐ¾ß´Â ÇâÈÄ ¸î ³âµ¿¾È ºü¸£°Ô ¼ºÀåÇÒ °ÍÀ¸·Î º¸ÀÔ´Ï´Ù.

Áö¿ªº° Àü¸Á

Áö¿ªº°·Î´Â ºÏ¹Ì, À¯·´, ¾Æ½Ã¾ÆÅÂÆò¾ç, LAMEA·Î ±¸ºÐµÇ¸ç, 2022³â¿¡´Â ºÏ¹Ì°¡ ½ÃÀå¿¡¼­ °¡Àå ³ôÀº ¸ÅÃâ Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ºÏ¹Ì¿¡´Â ±ÝÀ¶, ÀüÀÚ»ó°Å·¡, ÀÇ·á, ±â¼ú µî ¸¹Àº µ¥ÀÌÅÍ Áý¾àÀû »ê¾÷ÀÌ Á¸ÀçÇÕ´Ï´Ù. ÀÌ·¯ÇÑ »ê¾÷Àº È¿À²ÀûÀÎ µ¥ÀÌÅÍ °ü¸® ¼Ö·ç¼Ç¿¡ Å©°Ô ÀÇÁ¸Çϰí ÀÖ½À´Ï´Ù. ¹æ´ëÇÑ ¾çÀÇ µ¥ÀÌÅ͸¦ ºü¸£°Ô ó¸®ÇÒ ¼ö ÀÖ´Â º¤ÅÍ µ¥ÀÌÅͺ£À̽º´Â ÀÌ·¯ÇÑ »ê¾÷¿¡¼­ Á¡Á¡ ´õ ¸¹ÀÌ »ç¿ëµÇ°í ÀÖ½À´Ï´Ù. µ¥ÀÌÅÍ ±â¹Ý ÀÇ»ç°áÁ¤¿¡ ´ëÇÑ Á߿伺ÀÌ Ä¿Áö¸é¼­ ºÏ¹Ì ±â¾÷µéÀº °­·ÂÇÑ ºñÁî´Ï½º ÀÎÅÚ¸®Àü½º ¹× ºÐ¼® µµ±¸¿¡ ´ëÇÑ ÅõÀÚ¸¦ ´Ã¸®°í ÀÖ½À´Ï´Ù. µû¶ó¼­ ÀÌ ºÐ¾ß¿¡ ´ëÇÑ ¼ö¿ä´Â Áõ°¡ÇÒ °ÍÀ¸·Î º¸ÀÔ´Ï´Ù.

¸ñÂ÷

Á¦1Àå ½ÃÀå ¹üÀ§¿Í Á¶»ç ¹æ¹ý

Á¦2Àå ½ÃÀå ¿ä¶÷

Á¦3Àå ½ÃÀå °³¿ä

Á¦4Àå °æÀï ºÐ¼® - ¼¼°è

Á¦5Àå ¼¼°èÀÇ º¤ÅÍ µ¥ÀÌÅͺ£À̽º ½ÃÀå : Á¦°øº°

Á¦6Àå ¼¼°èÀÇ º¤ÅÍ µ¥ÀÌÅͺ£À̽º ½ÃÀå : ±â¼úº°

Á¦7Àå ¼¼°èÀÇ º¤ÅÍ µ¥ÀÌÅͺ£À̽º ½ÃÀå : ¾÷°èº°

Á¦8Àå ¼¼°èÀÇ º¤ÅÍ µ¥ÀÌÅͺ£À̽º ½ÃÀå : Áö¿ªº°

Á¦9Àå ±â¾÷ °³¿ä

Á¦10Àå ½ÃÀåÀÇ ¼º°ø Çʼö Á¶°Ç

LSH
¿µ¹® ¸ñÂ÷

¿µ¹®¸ñÂ÷

The Global Vector Database Market size is expected to reach $6.4 billion by 2030, rising at a market growth of 22.3% CAGR during the forecast period.

The IT and ITeS sector extensively leverage these databases for handling vast amounts of data. Thus, IT and ITeS segment acquired $442.5 million in 2022. These databases offer high-performance solutions for data processing and analytics, empowering companies in this segment to manage, analyze, and derive insights from intricate and high-dimensional datasets. This capability is crucial for diverse applications in software development, data analysis, and customer-oriented solutions. These aspects are beneficial for increasing demand in the segment. Some of the factors impacting the market are the rise of AI and machine learning, need for high performance across sectors, and high cost of implementation and infrastructure.

Integrating AI and ML tools directly within the database environment streamlines the analytics process by eliminating the need for extensive data preprocessing. This means that analytical models can operate on the raw, high-dimensional data stored in these databases, avoiding time-consuming and resource-intensive data preparation stages. As a result, it simplifies the overall data pipeline, allowing organizations to extract insights more rapidly and efficiently. This real-time analysis facilitates quicker decision-making, allowing organizations to respond promptly to changing conditions and emerging trends. Additionally, the high-performance analytics offered by these databases, attributed to their optimized data structures and query processing, play a pivotal role in various sectors. In finance, real-time analysis is vital for making split-second decisions. These databases enable swift analysis of operational data, ensuring streamlined and efficient processes. Owing to these factors, the market will expand rapidly in the coming years.

However, Acquiring the necessary infrastructure, whether it involves high-performance servers, substantial memory, or specific processing units (e.g., GPUs for accelerating computations), can incur substantial upfront costs. For instance, in-memory databases necessitate a robust infrastructure with ample memory capacity to store and process data directly in memory. These specialized hardware requirements can significantly escalate the initial setup costs. The perceived high costs may cause hesitation, particularly when evaluating the return on investment (ROI) and the immediate value the database can provide to the organization. Thus, these aspects are expected to restrain the growth of the market in the coming years.

Offering Outlook

Based on offering, the market is segmented into solutions and services. The solutions segment acquired the highest revenue share in the market in 2022. The solution segment has grown substantially due to the vast use cases across industries. As organizations grapple with large and complex datasets, the need for efficient data management solutions has surged. These databases offer solutions that cater to diverse applications, from machine learning and AI to geospatial data analysis, time-series data processing, graph data management, and more. The adaptability of These databases to multiple use cases has propelled their growth within the solution segment. As a result, the segment will witness increased growth in the future.

Technology Outlook

On the basis of technology, the market is divided into natural language processing, computer vision, and recommendation systems. In 2022, the computer vision segment witnessed a substantial revenue share in the market. The proliferation of image and video data due to the widespread use of devices such as smartphones, surveillance cameras, and IoT devices has led to an exponential increase in data volume. Computer vision applications generate huge amounts of visual data that require efficient storage, retrieval, and analysis, which vector databases are well-suited to manage due to their ability to handle high-dimensional data efficiently. Therefore, the segment is expected to proliferate in the coming years.

Vertical Outlook

Based on vertical, the market is divided into BFSI, retail & e-commerce, healthcare, IT & ITeS, media & entertainment, manufacturing, and others. The BFSI segment procured a substantial revenue share in the market in 2022. BFSI organizations deal with vast amounts of transactional and customer data. The use of vector databases allows for real-time analysis of this data, offering insights into customer behavior, risk assessment, and fraud detection. These databases empower financial institutions to quickly identify patterns and trends, enabling personalized services and more accurate risk evaluations. The BFSI sector deals with intricate data structures, including time series, complex financial models, and relational data. Therefore, the segment will expand rapidly in the upcoming years.

Regional Outlook

By region, the market is segmented into North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America segment acquired the highest revenue share in the market. North America houses many data-intensive industries, such as finance, e-commerce, healthcare, and technology. These sectors rely heavily on efficient data management solutions. Vector databases, with their capabilities to process vast amounts of data quickly, have become increasingly popular in these industries. With a growing emphasis on data-driven decision-making, businesses in North America have been increasingly investing in robust business intelligence and analytics tools. Thus, there will be increased demand in the segment.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Elastic N.V., Alibaba Cloud (Alibaba Group Holding Limited), Amazon Web Services, Inc. (Amazon.com, Inc.), Google LLC (Alphabet Inc.), DataStax, Inc., GSI Technology, Inc., Clarifai, Inc., Pinecone Systems, Inc., Rockset, Inc.

Scope of the Study

Market Segments covered in the Report:

By Offering

By Technology

By Vertical

By Geography

Companies Profiled

Unique Offerings from KBV Research

Table of Contents

Chapter 1. Market Scope & Methodology

Chapter 2. Market at a Glance

Chapter 3. Market Overview

Chapter 4. Competition Analysis - Global

Chapter 5. Global Vector Database Market by Offering

Chapter 6. Global Vector Database Market by Technology

Chapter 7. Global Vector Database Market by Vertical

Chapter 8. Global Vector Database Market by Region

Chapter 9. Company Profiles

Chapter 10. Winning Imperatives of Vector Database Market

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