¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS) ½ÃÀå
Database Management Systems (DBMS)
»óǰÄÚµå : 1760909
¸®¼­Ä¡»ç : Global Industry Analysts, Inc.
¹ßÇàÀÏ : 2025³â 07¿ù
ÆäÀÌÁö Á¤º¸ : ¿µ¹® 158 Pages
 ¶óÀ̼±½º & °¡°Ý (ºÎ°¡¼¼ º°µµ)
US $ 5,850 £Ü 8,101,000
PDF (Single User License) help
PDF º¸°í¼­¸¦ 1¸í¸¸ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. Àμâ´Â °¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.
US $ 17,550 £Ü 24,303,000
PDF (Global License to Company and its Fully-owned Subsidiaries) help
PDF º¸°í¼­¸¦ µ¿ÀÏ ±â¾÷ÀÇ ¸ðµç ºÐÀÌ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. Àμâ´Â °¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.


Çѱ۸ñÂ÷

µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS) ¼¼°è ½ÃÀåÀº 2030³â±îÁö 1,546¾ï ´Þ·¯¿¡ À̸¦ Àü¸Á

2024³â¿¡ 795¾ï ´Þ·¯·Î ÃßÁ¤µÇ´Â µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS) ¼¼°è ½ÃÀåÀº 2024-2030³â°£ CAGR 11.7%·Î ¼ºÀåÇÏ¿© 2030³â¿¡´Â 1,546¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. º» º¸°í¼­¿¡¼­ ºÐ¼®ÇÑ ºÎ¹® Áß ÇϳªÀÎ ¼ÒÇÁÆ®¿þ¾î´Â CAGR 12.6%¸¦ ³ªÅ¸³»°í, ºÐ¼® ±â°£ Á¾·á½Ã¿¡´Â 1,177¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. Çϵå¿þ¾î ºÐ¾ßÀÇ ¼ºÀå·üÀº ºÐ¼® ±â°£Áß CAGR 9.3%·Î ÃßÁ¤µË´Ï´Ù.

¹Ì±¹ ½ÃÀåÀº 209¾ï ´Þ·¯·Î ÃßÁ¤, Áß±¹Àº CAGR 15.9%·Î ¼ºÀå ¿¹Ãø

¹Ì±¹ÀÇ µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS) ½ÃÀåÀº 2024³â¿¡ 209¾ï ´Þ·¯·Î ÃßÁ¤µË´Ï´Ù. ¼¼°è 2À§ °æÁ¦´ë±¹ÀÎ Áß±¹Àº 2030³â±îÁö 359¾ï ´Þ·¯ ±Ô¸ð¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµÇ¸ç, ºÐ¼® ±â°£ÀÎ 2024-2030³â CAGRÀº 15.9%·Î ¿¹»óµË´Ï´Ù. ±âŸ ÁÖ¸ñÇØ¾ß ÇÒ Áö¿ªº° ½ÃÀåÀ¸·Î´Â ÀϺ»°ú ij³ª´Ù°¡ ÀÖÀ¸¸ç, ºÐ¼® ±â°£Áß CAGRÀº °¢°¢ 8.6%¿Í 9.5%¸¦ º¸ÀÏ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. À¯·´¿¡¼­´Â µ¶ÀÏÀÌ CAGR 8.9%¸¦ º¸ÀÏ Àü¸ÁÀÔ´Ï´Ù.

¼¼°è µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS) ½ÃÀå - ÁÖ¿ä µ¿Çâ ¹× ½ÃÀå ¼ºÀå ÃËÁø¿äÀÎ »ìÆìº¸±â

µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS)ÀÌ Çö´ë µ¥ÀÌÅÍ ±â¹Ý ±â¾÷ÀÇ ±â¹ÝÀÌ µÇ´Â ÀÌÀ¯´Â ¹«¾ùÀϱî?

µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS)Àº ÀÇ»ç°áÁ¤, ¿î¿µ, Àü·« ¼ö¸³¿¡ µ¥ÀÌÅÍÀÇ ÈûÀ» Ȱ¿ëÇϰíÀÚ ÇÏ´Â Á¶Á÷¿¡ ÇʼöÀûÀÎ µµ±¸°¡ µÇ¾ú½À´Ï´Ù. ÇÏÁö¸¸ DBMS ¼Ö·ç¼ÇÀÌ ¾÷Á¾°ú ¿ëµµ¸¦ ºÒ¹®Çϰí Áß¿äÇÑ ÀÌÀ¯´Â ¹«¾ùÀΰ¡? µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛÀº Á¶Á÷ÀÌ µ¥ÀÌÅͺ£À̽º¸¦ Á¤ÀÇ, »ý¼º, °ü¸®, Á¶ÀÛÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇÏ´Â ¼ÒÇÁÆ®¿þ¾î ¼Ö·ç¼ÇÀ¸·Î, µ¥ÀÌÅÍÀÇ ¹«°á¼º, º¸¾È, Á¢±Ù¼ºÀ» º¸ÀåÇϸ鼭 µ¥ÀÌÅ͸¦ ÀúÀå, °Ë»ö, Á¶ÀÛÇÒ ¼ö ÀÖ´Â ±¸Á¶È­µÈ ¹æ¹ýÀ» Á¦°øÇÕ´Ï´Ù. DBMS ¼Ö·ç¼ÇÀº ºñÁî´Ï½º Æ®·£Àè¼Ç, µ¥ÀÌÅÍ ¿þ¾îÇϿ콺, ºÐ¼® µî ´Ù¾çÇÑ ÀÌ¿ë »ç·Ê¿¡¼­ ±¸Á¶È­, ¹Ý±¸Á¶È­, ºñÁ¤Çü µ¥ÀÌÅ͸¦ °ü¸®ÇÏ´Â µ¥ »ç¿ëµÇ¸ç, Á¤º¸ ½Ã½ºÅÛÀÇ ÁßÃßÀûÀÎ ¿ªÇÒÀ» ¼öÇàÇÏ¿© ¾÷¹« ÇÁ·Î¼¼½ººÎÅÍ º¹ÀâÇÑ ºÐ¼® ¿öÅ©·Îµå±îÁö º¹ÀâÇÑ ºÐ¼® ¿öÅ©·Îµå±îÁö ¸ðµç °ÍÀ» Áö¿øÇÕ´Ï´Ù.

µðÁöÅÐ ÀÎÅÍ·¢¼Ç, IoT ±â±â, ¼Ò¼È ¹Ìµð¾î, ¿£ÅÍÇÁ¶óÀÌÁî ¿ëµµ¸¦ ÅëÇØ ±â¾÷ÀÌ ´ë·®ÀÇ µ¥ÀÌÅ͸¦ Áö¼ÓÀûÀ¸·Î »ý¼ºÇÔ¿¡ µû¶ó DBMS ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä°¡ ±ÞÁõÇϰí ÀÖ½À´Ï´Ù. ÀÌ µ¥ÀÌÅÍ´Â °í°´ Çൿ, ½ÃÀå µ¿Çâ, ¾÷¹« È¿À²¼º¿¡ ´ëÇÑ ±íÀº ÅëÂû·ÂÀ» Á¦°øÇÒ ¼ö ÀÖ´Â ±ÍÁßÇÑ ÀÚ»êÀÔ´Ï´Ù. ±×·¯³ª °­·ÂÇÑ DBMS°¡ ¾ø´Ù¸é ÀÌ·¯ÇÑ µ¥ÀÌÅ͸¦ °ü¸®Çϰí Ȱ¿ëÇÏ´Â °ÍÀº ½±Áö ¾ÊÀº ÀÏÀÔ´Ï´Ù. ÃֽŠDBMS Ç÷§ÆûÀº Á¶Á÷ÀÌ µ¥ÀÌÅ͸¦ È¿À²ÀûÀ¸·Î ÀúÀåÇϰí, ½Å¼ÓÇÏ°Ô Äõ¸®¸¦ ¼öÇàÇϸç, ´ë±Ô¸ð ¹èÆ÷¿¡¼­µµ µ¥ÀÌÅÍÀÇ Àϰü¼º°ú °¡¿ë¼ºÀ» À¯ÁöÇÒ ¼ö ÀÖ´Â ÅøÀ» Á¦°øÇÕ´Ï´Ù. ¶ÇÇÑ, Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ°ú ÇÏÀ̺긮µå ȯ°æÀ¸·ÎÀÇ ÀüȯÀº DBMS ¼Ö·ç¼ÇÀÇ ±â´ÉÀ» È®ÀåÇÏ¿© ±â¾÷ÀÌ ´õ ³ôÀº È®À强, À¯¿¬¼º ¹× ºñ¿ë È¿À²¼ºÀ» ´Þ¼ºÇÒ ¼ö ÀÖµµ·Ï µ½½À´Ï´Ù. ±â¾÷µéÀÌ µ¥ÀÌÅÍ Á᫐ Àü·«À» äÅÃÇÏ´Â Ãß¼¼°¡ °­È­µÇ°í ÀÖ´Â °¡¿îµ¥, DBMS ¼Ö·ç¼ÇÀº µðÁöÅÐ ÀüȯÀÇ ÇÙ½ÉÀÌ µÇ¾î ±â¾÷ÀÌ µ¥ÀÌÅÍ ÀÚ»êÀÇ ÀáÀç·ÂÀ» ÃÖ´ëÇÑ È°¿ëÇÒ ¼ö ÀÖµµ·Ï µ½°í ÀÖ½À´Ï´Ù.

±â¼úÀÇ ¹ßÀüÀº µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛÀÇ ´É·ÂÀ» ¾î¶»°Ô Çâ»ó½Ã۰í Àִ°¡?

µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ ½ÃÀåÀº ÀÌ·¯ÇÑ Ç÷§ÆûÀÇ ¼º´É, È®À强 ¹× ¹ü¿ë¼ºÀ» Çâ»ó½ÃŰ´Â Áß¿äÇÑ ±â¼ú ¹ßÀüÀ» ¸ñ°ÝÇß½À´Ï´Ù. ±×·¸´Ù¸é ÀÌ·¯ÇÑ ¹ßÀüÀ» ÁÖµµÇÏ´Â ÁÖ¿ä Çõ½ÅÀº ¹«¾ùÀΰ¡? °¡Àå ¿µÇâ·Â ÀÖ´Â ¹ßÀü Áß Çϳª´Â Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê ¹× ºÐ»ê µ¥ÀÌÅͺ£À̽º ¾ÆÅ°ÅØÃ³ÀÇ ºÎ»óÀÔ´Ï´Ù. Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê DBMS ¼Ö·ç¼ÇÀº Ŭ¶ó¿ìµå ȯ°æÀ» ÃÖ´ëÇÑ È°¿ëÇÒ ¼ö ÀÖµµ·Ï ¼³°èµÇ¾úÀ¸¸ç, ¿Âµð¸Çµå È®À强, ÀÚµ¿ ¹é¾÷, ¼¼°è ºÐ»ê µîÀÇ ±â´ÉÀ» Á¦°øÇÕ´Ï´Ù. À̸¦ ÅëÇØ ±â¾÷Àº ¿öÅ©·Îµå¿¡ µû¶ó µ¿ÀûÀ¸·Î È®ÀåµÇ´Â µ¥ÀÌÅͺ£À̽º¸¦ µµÀÔÇÒ ¼ö ÀÖÀ¸¸ç, ÇÇÅ© ½Ã »ç¿ë·®¿¡µµ ³ôÀº °¡¿ë¼º°ú ¼º´ÉÀ» º¸ÀåÇÒ ¼ö ÀÖ½À´Ï´Ù. Ŭ·¯½ºÅÍ¿¡ µ¥ÀÌÅ͸¦ ºÐ»ê½ÃÅ´À¸·Î½á ¼öÆòÀû ½ºÄÉÀϸµÀ» Áö¿øÇÕ´Ï´Ù. ÀÌ ¾ÆÅ°ÅØÃ³¸¦ ÅëÇØ ±â¾÷Àº ¸Å¿ì Å« ±Ô¸ðÀÇ µ¥ÀÌÅÍ ¼¼Æ®¸¦ °ü¸®ÇÏ°í ºü¸¥ Æ®·£Àè¼ÇÀ» ó¸®ÇÒ ¼ö ÀÖ¾î ÀüÀÚ»ó°Å·¡, ¼Ò¼È ¹Ìµð¾î, ½Ç½Ã°£ ºÐ¼® µîÀÇ ¿ëµµ¿¡ ÀûÇÕÇÕ´Ï´Ù.

¶Ç ´Ù¸¥ Áß¿äÇÑ Çõ½ÅÀº ÀΰøÁö´É(AI)°ú ¸Ó½Å·¯´×(ML)À» DBMS ¼Ö·ç¼Ç¿¡ ÅëÇÕÇÏ´Â °ÍÀ¸·Î, AI ±â¹Ý DBMS Ç÷§ÆûÀº À妽Ì, Äõ¸® ÃÖÀûÈ­, ÀÌ»ó °¨Áö µî ÀÏ»óÀûÀÎ °ü¸® ÀÛ¾÷À» ÀÚµ¿È­ÇÏ¿© ¼öµ¿ °³ÀÔÀÇ Çʿ伺À» ÁÙÀ̰í, ÀÎÀû ¿À·ùÀÇ À§ÇèÀ» ÃÖ¼ÒÈ­ÇÕ´Ï´Ù. À§ÇèÀ» ÃÖ¼ÒÈ­ÇÒ ¼ö ÀÖ½À´Ï´Ù. ¸Ó½Å·¯´× ¾Ë°í¸®ÁòÀº Äõ¸® ÆÐÅÏÀ» ºÐ¼®Çϰí, ¸®¼Ò½º ÇÒ´çÀ» ÃÖÀûÈ­Çϰí, ÀáÀçÀûÀÎ ¼º´É ¹®Á¦¸¦ ¿¹ÃøÇÏ¿© DBMS°¡ º¯È­ÇÏ´Â ¿öÅ©·Îµå¿¡ ÀûÀÀÇÒ ¼ö ÀÖµµ·Ï ½º½º·Î Á¶Á¤ÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Áö´ÉÇü ÀÚµ¿È­¸¦ ÅëÇØ ±â¾÷Àº ÃÖÀûÀÇ µ¥ÀÌÅͺ£À̽º ¼º´ÉÀ» À¯ÁöÇϰí, ´Ù¿îŸÀÓÀ» ÁÙÀ̸ç, ¿î¿µ È¿À²¼ºÀ» Çâ»ó½Ãų ¼ö ÀÖ½À´Ï´Ù. ¶ÇÇÑ, AI¿Í MLÀº DBMS Ç÷§Æû ³» µ¥ÀÌÅÍ º¸¾ÈÀ» °­È­Çϱâ À§ÇØ »ç¿ëµÇ¾î ½Ç½Ã°£ À§Çù °¨Áö ¹× ÀáÀçÀû º¸¾È Ä§ÇØ¿¡ ´ëÇÑ ÀÚµ¿È­µÈ ´ëÀÀÀ» Á¦°øÇÕ´Ï´Ù.

¸ÖƼ¸ðµ¨ µ¥ÀÌÅͺ£À̽º¿Í Æú¸®±×·ÎÆ® ÆÛ½Ã½ºÅϽº µ¥ÀÌÅͺ£À̽ºÀÇ µîÀåÀº ÃֽŠDBMS ¼Ö·ç¼ÇÀÇ ±â´ÉÀ» ¿ÏÀüÈ÷ ¹Ù²Ù¾î ³õ¾Ò½À´Ï´Ù. ¸ÖƼ¸ðµ¨ µ¥ÀÌÅͺ£À̽º´Â ´ÜÀÏ Ç÷§Æû ³»¿¡¼­ °ü°èÇü, ¹®¼­, ±×·¡ÇÁ, ۰ª µî ´Ù¾çÇÑ µ¥ÀÌÅÍ ¸ðµ¨À» Áö¿øÇϹǷÎ, Á¶Á÷Àº º°µµÀÇ µ¥ÀÌÅͺ£À̽º¸¦ µµÀÔÇÏÁö ¾Ê°íµµ °¢ ÀÌ¿ë »ç·Ê¿¡ °¡Àå ÀûÇÕÇÑ ¸ðµ¨À» »ç¿ëÇÒ ¼ö ÀÖ½À´Ï´Ù. Æú¸®±×·ÎÆ® ÆÛ½Ã½ºÅϽº(Polygrot Persistence)´Â ÀÌ·¯ÇÑ °³³äÀ» ´õ¿í ¹ßÀü½ÃÄÑ ´ÜÀÏ ¿ëµµ ¾ÆÅ°ÅØÃ³ ³»¿¡¼­ ¼­·Î ´Ù¸¥ µ¥ÀÌÅͺ£À̽º¸¦ °øÁ¸½ÃÅ´À¸·Î½á ±â¾÷ÀÌ ¼­·Î ´Ù¸¥ À¯ÇüÀÇ µ¥ÀÌÅÍ¿Í ¿öÅ©·Îµå¿¡ ƯȭµÈ µ¥ÀÌÅͺ£À̽º¸¦ Ȱ¿ëÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇÕ´Ï´Ù. ÀÌ·¯ÇÑ ¹ßÀüÀº ±â¾÷ÀÌ ´Ù¾çÇÑ µ¥ÀÌÅÍ À¯ÇüÀ» ó¸®Çϰí, µ¥ÀÌÅÍ ¾×¼¼½º ¹× °Ë»ö ½Ã°£À» °³¼±Çϸç, µ¥ÀÌÅÍ °ü¸® ÀÎÇÁ¶ó¸¦ °£¼ÒÈ­ÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇÕ´Ï´Ù. ¸ÖƼ ¸ðµ¨ ¹× Æú¸®±×·ÎÆ® ¿µ±¸ µ¥ÀÌÅͺ£À̽ºÀÇ Ã¤ÅÃÀº Á¶Á÷ÀÌ º¹ÀâÇÑ µ¥ÀÌÅÍ °ü°è °ü¸®, °í±Þ ºÐ¼® Áö¿ø ¶Ç´Â IoT ¼¾¼­ ÆÇµ¶°ªÀ̳ª ¼Ò¼È ¹Ìµð¾î ÄÁÅÙÃ÷¿Í °°Àº ºñÁ¤Çü µ¥ÀÌÅÍ Ã³¸®°¡ ÇÊ¿äÇÑ È¯°æ¿¡¼­ ƯÈ÷ Å« °¡Ä¡¸¦ ¹ßÈÖÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ±â¼ú Çõ½ÅÀº DBMS ¼Ö·ç¼ÇÀÇ ¿ª·®À» ÃÑüÀûÀ¸·Î Çâ»ó½ÃÄÑ ´Ù¾çÇϰí ÁøÈ­ÇÏ´Â µ¥ÀÌÅÍ ¿ä±¸¿¡ ´ëÀÀÇÒ ¼ö ÀÖ´Â ÀûÀÀ¼º, È®À强, È¿À²¼ºÀ» ³ôÀ̰í ÀÖ½À´Ï´Ù.

¾î¶² ½ÃÀå µ¿ÇâÀÌ ´Ù¾çÇÑ ºÐ¾ß¿¡¼­ µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛÀÇ Ã¤ÅÃÀ» ÃËÁøÇϰí Àִ°¡?

ÁøÈ­ÇÏ´Â Á¶Á÷ÀÇ ¿ä±¸¿Í Àü·«Àû ÀÚ»êÀ¸·Î¼­ µ¥ÀÌÅÍÀÇ Á߿伺ÀÌ ³ô¾ÆÁü¿¡ µû¶ó ´Ù¾çÇÑ ºÐ¾ß¿¡¼­ µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ µµÀÔÀÌ Áõ°¡Çϰí ÀÖ½À´Ï´Ù. °¡Àå ´«¿¡ ¶ç´Â Æ®·»µå Áß Çϳª´Â ÇÏÀ̺긮µå Ŭ¶ó¿ìµå¿Í ¸ÖƼ Ŭ¶ó¿ìµå µµÀÔ¿¡ ´ëÇÑ °ü½ÉÀÌ ³ô¾ÆÁö°í ÀÖ´Ù´Â Á¡ÀÔ´Ï´Ù. ±â¾÷ÀÌ ¿©·¯ Ŭ¶ó¿ìµå °ø±ÞÀÚ¸¦ Ȱ¿ëÇϰí On-Premise ÀÎÇÁ¶ó¿Í Ŭ¶ó¿ìµå ȯ°æÀ» ÅëÇÕÇÔ¿¡ µû¶ó, ÇÏÀ̺긮µå ¹× ¸ÖƼ Ŭ¶ó¿ìµå ¾ÆÅ°ÅØÃ³ Àü¹Ý¿¡ °ÉÃÄ µ¥ÀÌÅͺ£À̽º¸¦ °ü¸®ÇÏ´Â °ÍÀÌ Áß¿äÇÑ °úÁ¦°¡ µÇ°í ÀÖ½À´Ï´Ù. ÇÏÀ̺긮µå ¹× ¸ÖƼ Ŭ¶ó¿ìµå ±¸ÃàÀ» Áö¿øÇÏ´Â DBMS ¼Ö·ç¼ÇÀ» ÅëÇØ ±â¾÷Àº ¿øÈ°ÇÑ µ¥ÀÌÅÍ ÅëÇÕÀ» ½ÇÇöÇϰí, µ¥ÀÌÅÍ Àϰü¼ºÀ» À¯ÁöÇϸç, ´Ù¾çÇÑ È¯°æ¿¡¼­ ¼º´ÉÀ» ÃÖÀûÈ­ÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Ãß¼¼´Â ÆÛºí¸¯, ÇÁ¶óÀ̺ø, ÇÏÀ̺긮µå Ŭ¶ó¿ìµå Àü¹Ý¿¡ °ÉÃÄ µ¥ÀÌÅͺ£À̽º¸¦ À¯¿¬ÇÏ°Ô ¹èÆ÷ÇÏ°í °ü¸®ÇÒ ¼ö Àִ Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê DBMS Ç÷§Æû°ú DBaaS(database-as-a-service) ¼­ºñ½º µµÀÔÀ» ÃËÁøÇϰí ÀÖ½À´Ï´Ù. Çϰí ÀÖ½À´Ï´Ù. On-Premise ȯ°æ¿¡¼­ ±â¹Ð µ¥ÀÌÅ͸¦ °ü¸®Çϸ鼭µµ Ŭ¶ó¿ìµå ±â¹ÝÀÇ È®À强°ú ÀçÇØº¹±¸ ±â´ÉÀ» Ȱ¿ëÇÒ ¼ö ÀÖ´Ù´Â Á¡ÀÌ ÀÌ·¯ÇÑ Ãß¼¼ÀÇ Áß¿äÇÑ ¿øµ¿·ÂÀÌ µÇ°í ÀÖ½À´Ï´Ù.

DBMS ¼Ö·ç¼Ç µµÀÔÀ» ÃËÁøÇÏ´Â ¶Ç ´Ù¸¥ ÁÖ¿ä Æ®·»µå´Â µ¥ÀÌÅÍ ºÐ¼®°ú ºñÁî´Ï½º ÀÎÅÚ¸®Àü½º(BI)¿¡ ´ëÇÑ °ü½ÉÀÌ ³ô¾ÆÁö°í ÀÖ´Ù´Â Á¡ÀÔ´Ï´Ù. Á¶Á÷Àº Á¡Á¡ ´õ ¸¹Àº µ¥ÀÌÅ͸¦ Ȱ¿ëÇÏ¿© ½ÇÇà °¡´ÉÇÑ ÅëÂû·ÂÀ» ¾ò°í, ¾÷¹«¸¦ ÃÖÀûÈ­Çϰí, Àü·«Àû ÀÇ»ç°áÁ¤À» ³»¸®±â À§ÇØ µ¥ÀÌÅ͸¦ Ȱ¿ëÇϰí ÀÖ½À´Ï´Ù. ½Ç½Ã°£ ºÐ¼®, Àθ޸𸮠ó¸® ¹× ÅëÇÕ BI ÅøÀ» Áö¿øÇÏ´Â °í±Þ DBMS Ç÷§ÆûÀ» ÅëÇØ ±â¾÷Àº º¹ÀâÇÑ Äõ¸®¸¦ ½ÇÇàÇÏ°í ´ë±Ô¸ð µ¥ÀÌÅÍ ºÐ¼®À» ¼öÇàÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Ãß¼¼´Â °í°´ °æÇè Çâ»ó, ºñ¿ë Àý°¨, »õ·Î¿î ¼ºÀå ±âȸ ¹ß±¼À» À§ÇØ µ¥ÀÌÅÍ ±â¹Ý ÀλçÀÌÆ®°¡ ÇʼöÀûÀÎ ±ÝÀ¶, ÇコÄɾî, ¸®Å×ÀÏ µîÀÇ »ê¾÷¿¡¼­ ƯÈ÷ µÎµå·¯Áö¸ç, DBMS ¼Ö·ç¼Ç°ú Hadoop ¹× Apache Spark¿Í °°Àº ºòµ¥ÀÌÅÍ ±â¼ú°úÀÇ ÅëÇÕÀº ´ë±Ô¸ð µ¥ÀÌÅÍ ¼¼Æ®¸¦ ó¸®ÇÏ°í ºÐ¼®ÇÒ ¼ö ÀÖ´Â Á¶Á÷ÀÇ ¿ª·®À» °­È­ÇÕ´Ï´Ù. ¿¹Ãø ¸ðµ¨¸µ, ¸Ó½Å·¯´×, AI ±â¹Ý ÀÇ»ç°áÁ¤ Áö¿ø°ú °°Àº °í±Þ ºÐ¼®ÀÇ ÀÌ¿ë »ç·Ê¸¦ Áö¿øÇϱâ À§ÇØ Á¶Á÷ÀÌ ´ë±Ô¸ð µ¥ÀÌÅÍ ¼¼Æ®¸¦ ó¸®ÇÏ°í ºÐ¼®ÇÒ ¼ö ÀÖ´Â ¿ª·®À» ´õ¿í °­È­ÇÕ´Ï´Ù.

µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ µµÀÔÀº µ¥ÀÌÅÍ °Å¹ö³Í½º, º¸¾È, ÄÄÇöóÀ̾𽺿¡ ´ëÇÑ °ü½ÉÀÌ ³ô¾ÆÁö¸é¼­ ¿µÇâÀ» ¹Þ°í ÀÖ½À´Ï´Ù. °í°´ Á¤º¸, À繫 ±â·Ï, ÁöÀû Àç»ê±Ç µî ±â¾÷ÀÌ Ãë±ÞÇÏ´Â ±â¹Ð µ¥ÀÌÅÍÀÇ ¾çÀÌ Áõ°¡ÇÔ¿¡ µû¶ó µ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã¿Í ±ÔÁ¦ Áؼö¸¦ º¸ÀåÇÏ´Â °ÍÀÌ °¡Àå Áß¿äÇÑ °úÁ¦°¡ µÇ°í ÀÖ½À´Ï´Ù. ÃֽŠDBMS Ç÷§ÆûÀº ¾Ïȣȭ, ¿ªÇÒ ±â¹Ý ¾×¼¼½º Á¦¾î, ÀÚµ¿È­µÈ ÄÄÇöóÀ̾𽺠º¸°í¿Í °°Àº °­·ÂÇÑ º¸¾È ±â´ÉÀ» Á¦°øÇÏ¿© ¹«´Ü ¾×¼¼½º·ÎºÎÅÍ µ¥ÀÌÅ͸¦ º¸È£Çϰí, ÀÏ¹Ý µ¥ÀÌÅÍ º¸È£ ±ÔÁ¤(GDPR(EU °³ÀÎÁ¤º¸º¸È£±ÔÁ¤)), ͏®Æ÷´Ï¾Æ ¼ÒºñÀÚ °³ÀÎÁ¤º¸ º¸È£¹ý(CCPA), ÀǷẸÇèÀÇ È޴뼺 ¹× Ã¥ÀÓ¼ºÀ» º¸ÀåÇÕ´Ï´Ù. ÀǷẸÇè È޴뼺 ¹× Ã¥ÀÓ¿¡ °üÇÑ ¹ý·ü(HIPAA) µîÀÇ ±ÔÁ¤ Áؼö¸¦ Áö¿øÇÕ´Ï´Ù. ÄÄÇöóÀ̾𽺸¦ ÀÔÁõÇÏ°í °­·ÂÇÑ µ¥ÀÌÅÍ °Å¹ö³Í½º¸¦ À¯ÁöÇÏ´Â ´É·ÂÀº µ¥ÀÌÅÍ À¯ÃâÀ̳ª ÄÄÇöóÀ̾𽺠À§¹ÝÀÌ ½É°¢ÇÑ ÀçÁ¤Àû, ÆòÆÇ»óÀÇ ¿µÇâÀ» ¹ÌÄ¥ ¼ö ÀÖ´Â ±ÝÀ¶, ÀÇ·á, Á¤ºÎ µîÀÇ »ê¾÷¿¡¼­ ƯÈ÷ Áß¿äÇÕ´Ï´Ù. µ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã ±ÔÁ¦°¡ °è¼Ó ÁøÈ­ÇÔ¿¡ µû¶ó, º¸¾È°ú ÄÄÇöóÀ̾𽺸¦ ¿ì¼±½ÃÇÏ´Â DBMS ¼Ö·ç¼ÇÀÇ Ã¤ÅÃÀÌ Áõ°¡ÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.

¼¼°è µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ ½ÃÀåÀÇ ¼ºÀåÀ» °¡¼ÓÇÏ´Â ¿äÀÎÀº ¹«¾ùÀΰ¡?

¼¼°è µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ ½ÃÀåÀÇ ¼ºÀåÀº Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ äÅà Áõ°¡, ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸® ¼ö¿ä Áõ°¡, µ¥ÀÌÅͺ£À̽º ±â¼ú ¹ßÀü µî ¿©·¯ ¿äÀο¡ ÀÇÇØ ÁÖµµµÇ°í ÀÖ½À´Ï´Ù. ÁÖ¿ä ¼ºÀå ¿äÀÎ Áß Çϳª´Â Ŭ¶ó¿ìµå ¼­ºñ½º¿Í DBaaS(database-as-a-service)ÀÇ Ã¤ÅÃÀÌ È®´ëµÇ°í ÀÖ´Ù´Â Á¡ÀÔ´Ï´Ù. ±â¾÷µéÀÌ ´õ ³ôÀº È®À强, À¯¿¬¼º, ºñ¿ë È¿À²¼ºÀ» À§ÇØ ¿öÅ©·Îµå¸¦ Ŭ¶ó¿ìµå·Î ÀÌÀüÇÔ¿¡ µû¶ó ÇÏÀ̺긮µå ¹× ¸ÖƼ Ŭ¶ó¿ìµå ¹èÆ÷¸¦ Áö¿øÇÒ ¼ö Àִ Ŭ¶ó¿ìµå ±â¹Ý DBMS ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡Çϰí ÀÖ½À´Ï´Ù. °ü¸®Çü µ¥ÀÌÅͺ£À̽º ¼­ºñ½º¸¦ Á¦°øÇÏ¿© º¹ÀâÇÑ ÀÎÇÁ¶ó °ü¸®ÀÇ Çʿ伺À» ¾ø¾Ö°í, ±â¾÷Àº ¾ÖÇø®ÄÉÀÌ¼Ç °³¹ß°ú Çõ½Å¿¡ ÁýÁßÇÒ ¼ö ÀÖ½À´Ï´Ù. ¹°¸®Àû ÀÎÇÁ¶ó¿¡ ÅõÀÚÇÏÁö ¾Ê°íµµ Çʿ信 µû¶ó µ¥ÀÌÅͺ£À̽º¸¦ È®ÀåÇϰí, °ü¸® ÀÛ¾÷À» ÀÚµ¿È­Çϸç, °í°¡¿ë¼º ¹× ÀÚµ¿ ¹é¾÷°ú °°Àº °í±Þ ±â´ÉÀ» ÀÌ¿ëÇÒ ¼ö ÀÖ´Ù´Â Á¡ÀÌ ¸ðµç ±Ô¸ðÀÇ ±â¾÷¿¡¼­ DBaaS ¼Ö·ç¼Ç äÅÃÀ» ÃËÁøÇϰí ÀÖ½À´Ï´Ù.

¶Ç ´Ù¸¥ ÁÖ¿ä ¼ºÀå ¿äÀÎÀº ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸® ¹× ºÐ¼®¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡ÀÔ´Ï´Ù. ±â¾÷µéÀÌ °³ÀÎÈ­µÈ °æÇèÀ» Á¦°øÇϰí, °ø±Þ¸ÁÀ» ÃÖÀûÈ­Çϸç, ½Ç½Ã°£ ÀλçÀÌÆ®¸¦ ÅëÇØ ÀÇ»ç°áÁ¤À» °­È­Çϱâ À§ÇØ ³ë·ÂÇϸ鼭 ½Ç½Ã°£À¸·Î µ¥ÀÌÅ͸¦ ó¸®ÇÏ°í ºÐ¼®ÇÒ ¼ö ÀÖ´Â DBMS Ç÷§Æû¿¡ ´ëÇÑ ¿ä±¸°¡ Áõ°¡Çϰí ÀÖ½À´Ï´Ù. ½Ç½Ã°£ DBMS ¼Ö·ç¼ÇÀ» ÅëÇØ ±â¾÷Àº IoT ±â±â, ¼Ò¼È ¹Ìµð¾î ½ºÆ®¸², Æ®·£Àè¼Ç ½Ã½ºÅÛ¿¡¼­ »ý¼ºµÈ µ¥ÀÌÅ͸¦ ¼öÁýÇϰí ó¸®ÇÏ¿© Áï°¢ÀûÀÎ ÅëÂû·ÂÀ» ¾ò°í º¸´Ù ºü¸¥ ÀÀ´ä ½Ã°£À» È®º¸ÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ ±â´ÉÀº ÀüÀÚ»ó°Å·¡, ±ÝÀ¶, Åë½Å µî ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸®°¡ °í°´ °æÇè, »ç±â °¨Áö, ¾÷¹« È¿À²¼º¿¡ Å« ¿µÇâÀ» ¹ÌÄ¡´Â »ê¾÷¿¡ ƯÈ÷ À¯¿ëÇÕ´Ï´Ù. ½Ç½Ã°£ DBMS Ç÷§Æû°ú AI ¹× ¸Ó½Å·¯´× ¸ðµ¨°úÀÇ ÅëÇÕÀº ¿¹Ãø ¹× ¿¹ÁöÀû ÀλçÀÌÆ®¸¦ µµÃâÇÒ ¼ö ÀÖ´Â Á¶Á÷ÀÇ ¿ª·®À» ´õ¿í °­È­ÇÏ¿© ÀÌ·¯ÇÑ ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä¸¦ ÃËÁøÇϰí ÀÖ½À´Ï´Ù.

¼¼°è DBMS ½ÃÀåÀº µðÁöÅÐ Àüȯ°ú µ¥ÀÌÅÍ ±â¹Ý ºñÁî´Ï½º Àü·«¿¡ ´ëÇÑ °ü½ÉÀÌ ³ô¾ÆÁü¿¡ µû¶ó ÇýÅÃÀ» ´©¸®°í ÀÖ½À´Ï´Ù. DBMS ¼Ö·ç¼ÇÀº ±â¾÷ÀÌ µ¥ÀÌÅ͸¦ º¸´Ù È¿À²ÀûÀ¸·Î °ü¸®Çϰí, µ¥ÀÌÅÍ Ç°ÁúÀ» º¸ÀåÇϸç, °í±Þ ºÐ¼®À» Áö¿øÇÔÀ¸·Î½á ÀÌ·¯ÇÑ ³ë·ÂÀÇ Åä´ë¸¦ Á¦°øÇÕ´Ï´Ù. ÇÒ ¼ö ÀÖµµ·Ï ÇÔÀ¸·Î½á ÀÌ·¯ÇÑ ³ë·ÂÀÇ ±â¹ÝÀ» Á¦°øÇÕ´Ï´Ù. Àδõ½ºÆ®¸® 4.0, IoT, ½º¸¶Æ®½ÃƼÀÇ ºÎ»óÀ¸·Î Ä¿³ØÆ¼µå µð¹ÙÀ̽º ¹× ½º¸¶Æ® ½Ã½ºÅÛ¿¡¼­ »ý¼ºµÇ´Â ´ë·®ÀÇ µ¥ÀÌÅÍ, ´Ù¾çÇÑ µ¥ÀÌÅÍ, ¼Óµµ¸¦ ó¸®ÇÒ ¼ö ÀÖ´Â DBMS Ç÷§Æû¿¡ ´ëÇÑ ¼ö¿ä°¡ ´õ¿í Áõ°¡Çϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, µ¥ÀÌÅÍ ÅëÇÕ, ½Ã°¢È­, AI ±â¹Ý ºÐ¼®ÀÇ ¹ßÀüÀ¸·Î DBMS ¼Ö·ç¼ÇÀÇ ÀÌ¿ë »ç·Ê°¡ È®´ëµÇ°í ÀÖÀ¸¸ç, DBMS´Â Çö´ë µðÁöÅÐ »ýŰèÀÇ Áß¿äÇÑ ±¸¼º ¿ä¼Ò·Î ÀÚ¸® Àâ°í ÀÖ½À´Ï´Ù.

µ¥ÀÌÅͺ£À̽º ±â¼úÀÇ Áö¼ÓÀûÀÎ ¹ßÀü, µ¥ÀÌÅÍ È¯°æÀÇ º¹À⼺, ½Ç½Ã°£ ºÐ¼® ¹× ±ÔÁ¤ Áؼö¿¡ ´ëÇÑ °ü½É Áõ°¡·Î ÀÎÇØ ¼¼°è µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ ½ÃÀåÀº Áö¼ÓÀûÀÎ ¼ºÀå¼¼¸¦ º¸À̰í ÀÖ½À´Ï´Ù. ±â¼ú Çõ½Å, ½ÃÀå ¼ö¿ä, ÁøÈ­ÇÏ´Â µ¥ÀÌÅÍ Àü·«ÀÇ ¿ªµ¿ÀûÀÎ »óÈ£ ÀÛ¿ëÀº ½ÃÀåÀÇ ¹Ì·¡¸¦ Çü¼ºÇϰí, ±â¾÷ÀÌ µ¥ÀÌÅÍ °ü¸® ¿ª·®À» °­È­Çϰí, ¼º´ÉÀ» ÃÖÀûÈ­Çϸç, ´õ ³ôÀº ¹Îø¼º°ú °æÀï ¿ìÀ§¸¦ È®º¸ÇÒ ¼ö ÀÖ´Â »õ·Î¿î ±âȸ¸¦ Á¦°øÇÕ´Ï´Ù. ±â¾÷ÀÌ µ¥ÀÌÅ͸¦ Àü·«Àû ÀÚ»êÀ¸·Î °è¼Ó ¿ì¼±¼øÀ§¸¦ µÎ´Â °¡¿îµ¥, µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛÀº µ¥ÀÌÅÍ Áß½ÉÀÇ µðÁöÅÐ ¿¬°á ½Ã´ë¿¡¼­ ¼º°øÀ» À§ÇÑ ±âº» µµ±¸·Î ÀÚ¸®¸Å±èÇÒ °ÍÀ¸·Î º¸ÀÔ´Ï´Ù.

ºÎ¹®

ÄÄÆ÷³ÍÆ®(¼ÒÇÁÆ®¿þ¾î, Çϵå¿þ¾î);Àü°³(On-Premise, Ŭ¶ó¿ìµå);¾÷°èº°(ÀºÇà, ±ÝÀ¶¼­ºñ½º ¹× º¸Çè(BFSI), IT ¹× ÅÚ·¹ÄÞ, ¿î¼Û, Á¦Á¶, ÇコÄɾî, ±âŸ ¾÷°è)

Á¶»ç ´ë»ó ±â¾÷ ¿¹(ÃÑ 12°³»ç)

AI ÅëÇÕ

Global Industry Analysts´Â À¯È¿ÇÑ Àü¹®°¡ ÄÁÅÙÃ÷¿Í AIÅø¿¡ ÀÇÇØ¼­, ½ÃÀå Á¤º¸¿Í °æÀï Á¤º¸¸¦ º¯ÇõÇϰí ÀÖ½À´Ï´Ù.

Global Industry Analysts´Â LLM³ª ¾÷°è °íÀ¯ SLM¸¦ Á¶È¸ÇÏ´Â ÀϹÝÀûÀÎ ±Ô¹ü¿¡ µû¸£´Â ´ë½Å¿¡, ºñµð¿À ±â·Ï, ºí·Î±×, °Ë»ö ¿£Áø Á¶»ç, ¹æ´ëÇÑ ¾çÀÇ ±â¾÷, Á¦Ç°/¼­ºñ½º, ½ÃÀå µ¥ÀÌÅÍ µî, Àü ¼¼°è Àü¹®°¡·ÎºÎÅÍ ¼öÁýÇÑ ÄÁÅÙÃ÷ ¸®Æ÷ÁöÅ丮¸¦ ±¸ÃàÇß½À´Ï´Ù.

°ü¼¼ ¿µÇâ °è¼ö

Global Industry Analysts´Â º»»çÀÇ ±¹°¡, Á¦Á¶°ÅÁ¡, ¼öÃâÀÔ(¿ÏÁ¦Ç° ¹× OEM)À» ±â¹ÝÀ¸·Î ±â¾÷ÀÇ °æÀï·Â º¯È­¸¦ ¿¹ÃøÇß½À´Ï´Ù. ÀÌ·¯ÇÑ º¹ÀâÇÏ°í ´Ù¸éÀûÀÎ ½ÃÀå ¿ªÇÐÀº ¼öÀÍ¿ø°¡(COGS) Áõ°¡, ¼öÀͼº °¨¼Ò, °ø±Þ¸Á ÀçÆí µî ¹Ì½ÃÀû ¹× °Å½ÃÀû ½ÃÀå ¿ªÇÐ Áß¿¡¼­µµ ƯÈ÷ °æÀï»çµé¿¡°Ô ¿µÇâÀ» ¹ÌÄ¥ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.

¸ñÂ÷

Á¦1Àå Á¶»ç ¹æ¹ý

Á¦2Àå ÁÖ¿ä ¿ä¾à

Á¦3Àå ½ÃÀå ºÐ¼®

Á¦4Àå °æÀï

LSH
¿µ¹® ¸ñÂ÷

¿µ¹®¸ñÂ÷

Global Database Management Systems (DBMS) Market to Reach US$154.6 Billion by 2030

The global market for Database Management Systems (DBMS) estimated at US$79.5 Billion in the year 2024, is expected to reach US$154.6 Billion by 2030, growing at a CAGR of 11.7% over the analysis period 2024-2030. Software, one of the segments analyzed in the report, is expected to record a 12.6% CAGR and reach US$117.7 Billion by the end of the analysis period. Growth in the Hardware segment is estimated at 9.3% CAGR over the analysis period.

The U.S. Market is Estimated at US$20.9 Billion While China is Forecast to Grow at 15.9% CAGR

The Database Management Systems (DBMS) market in the U.S. is estimated at US$20.9 Billion in the year 2024. China, the world's second largest economy, is forecast to reach a projected market size of US$35.9 Billion by the year 2030 trailing a CAGR of 15.9% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 8.6% and 9.5% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 8.9% CAGR.

Global Database Management Systems (DBMS) Market - Key Trends & Growth Drivers Explored

Why Are Database Management Systems (DBMS) the Foundation of Modern Data-Driven Enterprises?

Database Management Systems (DBMS) have become indispensable tools for organizations seeking to harness the power of data for decision-making, operations, and strategic planning. But what exactly makes DBMS solutions so critical across industries and applications? A Database Management System is a software solution that enables organizations to define, create, manage, and interact with databases. It provides a structured way to store, retrieve, and manipulate data while ensuring data integrity, security, and accessibility. DBMS solutions are used to manage structured, semi-structured, and unstructured data across a variety of use cases, including business transactions, data warehousing, and analytics. They serve as the backbone of information systems, supporting everything from operational processes to complex analytical workloads.

The demand for DBMS solutions has surged as businesses continue to generate massive volumes of data through digital interactions, IoT devices, social media, and enterprise applications. This data is a valuable asset that can provide deep insights into customer behavior, market trends, and operational efficiency. However, without a robust DBMS, managing and utilizing such data becomes challenging. Modern DBMS platforms provide organizations with the tools to store data efficiently, query it rapidly, and maintain data consistency and availability even in large-scale deployments. Additionally, the shift towards cloud computing and hybrid environments has expanded the capabilities of DBMS solutions, enabling organizations to achieve greater scalability, flexibility, and cost-efficiency. As companies increasingly adopt data-driven strategies, DBMS solutions are becoming a cornerstone of digital transformation, empowering businesses to unlock the full potential of their data assets.

How Are Technological Advancements Elevating the Capabilities of Database Management Systems?

The database management systems market has witnessed significant technological advancements that have enhanced the performance, scalability, and versatility of these platforms. But what are the key innovations driving these developments? One of the most impactful advancements is the rise of cloud-native and distributed database architectures. Cloud-native DBMS solutions are designed to take full advantage of cloud environments, offering features such as on-demand scalability, automated backups, and global distribution. This enables organizations to deploy databases that scale dynamically with workloads, ensuring high availability and performance even during peak usage. Distributed databases, such as NoSQL and NewSQL databases, support horizontal scaling by spreading data across multiple nodes or clusters. This architecture allows businesses to manage extremely large datasets and handle high-velocity transactions, making it ideal for applications like e-commerce, social media, and real-time analytics.

Another critical innovation is the integration of artificial intelligence (AI) and machine learning (ML) into DBMS solutions. AI-powered DBMS platforms can automate routine administrative tasks, such as indexing, query optimization, and anomaly detection, reducing the need for manual intervention and minimizing the risk of human errors. Machine learning algorithms can analyze query patterns, optimize resource allocation, and predict potential performance issues, enabling the DBMS to self-tune and adapt to changing workloads. This intelligent automation helps organizations maintain optimal database performance, reduce downtime, and improve operational efficiency. Additionally, AI and ML are being used to enhance data security within DBMS platforms, providing real-time threat detection and automated responses to potential security breaches.

The emergence of multi-model and polyglot persistence databases has also transformed the capabilities of modern DBMS solutions. Multi-model databases support multiple data models-such as relational, document, graph, and key-value-within a single platform, allowing organizations to use the best model for each specific use case without deploying separate databases. Polyglot persistence takes this concept further by allowing different databases to coexist within a single application architecture, enabling organizations to leverage specialized databases for different types of data and workloads. These advancements are enabling businesses to handle diverse data types, improve data access and retrieval times, and simplify their data management infrastructure. The adoption of multi-model and polyglot persistence databases is particularly valuable in environments where organizations need to manage complex data relationships, support advanced analytics, or process unstructured data, such as IoT sensor readings or social media content. These technological innovations have collectively elevated the capabilities of DBMS solutions, making them more adaptable, scalable, and efficient in handling diverse and evolving data needs.

What Market Trends Are Driving the Adoption of Database Management Systems Across Various Sectors?

Several key market trends are shaping the adoption of database management systems across various sectors, reflecting the evolving needs of organizations and the increasing importance of data as a strategic asset. One of the most prominent trends is the increasing focus on hybrid and multi-cloud deployments. As businesses leverage multiple cloud providers and integrate on-premises infrastructure with cloud environments, managing databases across hybrid and multi-cloud architectures has become a critical challenge. DBMS solutions that support hybrid and multi-cloud deployments enable organizations to achieve seamless data integration, maintain data consistency, and optimize performance across diverse environments. This trend is driving the adoption of cloud-native DBMS platforms and database-as-a-service (DBaaS) offerings, which provide the flexibility to deploy and manage databases across public, private, and hybrid clouds. The ability to leverage cloud-based scalability and disaster recovery capabilities while maintaining control over sensitive data in on-premises environments is a key driver of this trend.

Another key trend driving the adoption of DBMS solutions is the growing emphasis on data analytics and business intelligence (BI). Organizations are increasingly using data to gain actionable insights, optimize operations, and drive strategic decision-making. Advanced DBMS platforms that support real-time analytics, in-memory processing, and integrated BI tools enable businesses to perform complex queries and analyze data at scale. This trend is particularly strong in industries such as finance, healthcare, and retail, where data-driven insights are essential for improving customer experiences, reducing costs, and identifying new growth opportunities. The integration of DBMS solutions with big data technologies-such as Hadoop and Apache Spark-is further enhancing the ability of organizations to process and analyze large datasets, supporting advanced analytics use cases like predictive modeling, machine learning, and AI-driven decision support.

The adoption of database management systems is also being influenced by the increasing focus on data governance, security, and compliance. As organizations handle growing volumes of sensitive data-such as customer information, financial records, and intellectual property-ensuring data privacy and regulatory compliance has become a top priority. Modern DBMS platforms offer robust security features, such as encryption, role-based access control, and automated compliance reporting, to protect data from unauthorized access and support adherence to regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Health Insurance Portability and Accountability Act (HIPAA). The ability to demonstrate compliance and maintain strong data governance is particularly important for industries such as finance, healthcare, and government, where data breaches or non-compliance can result in severe financial and reputational consequences. As data privacy regulations continue to evolve, the adoption of DBMS solutions that prioritize security and compliance is expected to increase.

What Factors Are Driving the Growth of the Global Database Management Systems Market?

The growth in the global database management systems market is driven by several factors, including the rising adoption of cloud computing, the increasing demand for real-time data processing, and advancements in database technology. One of the primary growth drivers is the growing adoption of cloud services and database-as-a-service (DBaaS) offerings. As businesses migrate their workloads to the cloud to achieve greater scalability, flexibility, and cost-efficiency, there is increasing demand for cloud-based DBMS solutions that can support hybrid and multi-cloud deployments. DBaaS platforms provide organizations with managed database services that eliminate the need for complex infrastructure management, enabling businesses to focus on application development and innovation. The ability to scale databases on-demand, automate administrative tasks, and access advanced features-such as high availability and automated backups-without investing in physical infrastructure is driving the adoption of DBaaS solutions among businesses of all sizes.

Another key growth driver is the rising demand for real-time data processing and analytics. As organizations strive to deliver personalized experiences, optimize supply chains, and enhance decision-making with real-time insights, there is a growing need for DBMS platforms that can process and analyze data in real time. Real-time DBMS solutions enable businesses to capture and process data from IoT devices, social media streams, and transactional systems as it is generated, providing immediate insights and enabling faster response times. This capability is particularly valuable for industries such as e-commerce, finance, and telecommunications, where real-time data processing can significantly impact customer experience, fraud detection, and operational efficiency. The integration of real-time DBMS platforms with AI and machine learning models is further enhancing the ability of organizations to derive predictive and prescriptive insights, driving demand for these solutions.

The global DBMS market is also benefiting from the increasing focus on digital transformation and data-driven business strategies. As organizations across industries embark on digital transformation initiatives, they are leveraging data to gain a competitive edge, innovate new products and services, and improve operational efficiency. DBMS solutions provide the foundation for these initiatives by enabling businesses to manage data more effectively, ensure data quality, and support advanced analytics. The rise of Industry 4.0, IoT, and smart city initiatives is further driving demand for DBMS platforms that can handle the high volume, variety, and velocity of data generated by connected devices and smart systems. Additionally, advancements in data integration, visualization, and AI-driven analytics are expanding the use cases for DBMS solutions, making them a critical component of modern digital ecosystems.

With ongoing advancements in database technology, the growing complexity of data environments, and the increasing emphasis on real-time analytics and compliance, the global database management systems market is poised for sustained growth. The dynamic interplay of technological innovation, market demand, and evolving data strategies is set to shape the future of the market, offering businesses new opportunities to enhance their data management capabilities, optimize performance, and achieve greater agility and competitiveness. As companies continue to prioritize data as a strategic asset, database management systems will remain a foundational tool for driving success in the data-driven and digitally connected era.

SCOPE OF STUDY:

The report analyzes the Database Management Systems (DBMS) market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:

Component (Software, Hardware); Deployment (On-Premise, Cloud); Vertical (BFSI, IT & Telecom, Transportation, Manufacturing, Healthcare, Other Verticals)

Geographic Regions/Countries:

World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; Spain; Russia; and Rest of Europe); Asia-Pacific (Australia; India; South Korea; and Rest of Asia-Pacific); Latin America (Argentina; Brazil; Mexico; and Rest of Latin America); Middle East (Iran; Israel; Saudi Arabia; United Arab Emirates; and Rest of Middle East); and Africa.

Select Competitors (Total 12 Featured) -

AI INTEGRATIONS

We're transforming market and competitive intelligence with validated expert content and AI tools.

Instead of following the general norm of querying LLMs and Industry-specific SLMs, we built repositories of content curated from domain experts worldwide including video transcripts, blogs, search engines research, and massive amounts of enterprise, product/service, and market data.

TARIFF IMPACT FACTOR

Our new release incorporates impact of tariffs on geographical markets as we predict a shift in competitiveness of companies based on HQ country, manufacturing base, exports and imports (finished goods and OEM). This intricate and multifaceted market reality will impact competitors by increasing the Cost of Goods Sold (COGS), reducing profitability, reconfiguring supply chains, amongst other micro and macro market dynamics.

TABLE OF CONTENTS

I. METHODOLOGY

II. EXECUTIVE SUMMARY

III. MARKET ANALYSIS

IV. COMPETITION

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