½ÃÀ庸°í¼­
»óǰÄÚµå
1744554

¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀå : ½ÃÀå ¿¹Ãø - µ¥ÀÌÅͺ£À̽º À¯Çüº°, Àü°³ ¹æ½Äº°, Á¶Á÷ ±Ô¸ðº°, ¿ëµµº°, ÃÖÁ¾ »ç¿ëÀÚº°, Áö¿ªº° ºÐ¼®(-2032³â)

Database Market Forecasts to 2032 - Global Analysis By Database Type (Relational Databases, Non-relational / NoSQL Databases, NewSQL Databases and Object-oriented Databases), Deployment Mode, Organization Size, Application, End User and By Geography

¹ßÇàÀÏ: | ¸®¼­Ä¡»ç: Stratistics Market Research Consulting | ÆäÀÌÁö Á¤º¸: ¿µ¹® 200+ Pages | ¹è¼Û¾È³» : 2-3ÀÏ (¿µ¾÷ÀÏ ±âÁØ)

    
    
    



¡Ø º» »óǰÀº ¿µ¹® ÀÚ·á·Î Çѱ۰ú ¿µ¹® ¸ñÂ÷¿¡ ºÒÀÏÄ¡ÇÏ´Â ³»¿ëÀÌ ÀÖÀ» °æ¿ì ¿µ¹®À» ¿ì¼±ÇÕ´Ï´Ù. Á¤È®ÇÑ °ËÅ並 À§ÇØ ¿µ¹® ¸ñÂ÷¸¦ Âü°íÇØÁֽñ⠹ٶø´Ï´Ù.

Stratistics MRC¿¡ µû¸£¸é ¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀåÀº 2025³â¿¡ 1,503¾ï ´Þ·¯·Î ÃßÁ¤µÇ°í, ¿¹Ãø ±â°£ Áß CAGR 16.2%·Î ¼ºÀåÇÒ Àü¸ÁÀ̸ç, 2032³â¿¡´Â 4,299¾ï ´Þ·¯¿¡ À̸¦ Àü¸ÁÀÔ´Ï´Ù.

µ¥ÀÌÅͺ£À̽º´Â ½Ã½ºÅÛ¿¡ ÀüÀÚÀûÀ¸·Î ÀúÀåµÇ´Â ±¸Á¶È­µÈ Á¤º¸ ¶Ç´Â µ¥ÀÌÅÍÀÇ Á¶Á÷È­µÈ Ä÷º¼ÇÀÔ´Ï´Ù. ´ëºÎºÐÀÇ °æ¿ì Å×À̺í, ·¹ÄÚµå, ÇʵåÀÇ Çü½ÄÀ¸·Î µ¥ÀÌÅ͸¦ È¿À²ÀûÀ¸·Î ÀúÀå, °ü¸®, °Ë»öÇÒ ¼ö ÀÖµµ·Ï ¼³°èµÇ¾î ÀÖ½À´Ï´Ù. µ¥ÀÌÅͺ£À̽º´Â ´ë·®ÀÇ µ¥ÀÌÅ͸¦ ´Ù·ç°í Á¤È®¼º, ¾ÈÀü¼º, Á¢±Ù¼ºÀ» È®º¸Çϱâ À§ÇØ »ç¿ëµË´Ï´Ù. µ¥ÀÌÅÍ »ðÀÔ, »èÁ¦, ¾÷µ¥ÀÌÆ®, Äõ¸® µî ´Ù¾çÇÑ ÀÛ¾÷À» Áö¿øÇÕ´Ï´Ù. Çö´ë µ¥ÀÌÅͺ£À̽º´Â °ü°èÇü µ¥ÀÌÅͺ£À̽º, ºñ°ü°èÇü µ¥ÀÌÅͺ£À̽º, ºÐ»êÇü µ¥ÀÌÅͺ£À̽º, Ŭ¶ó¿ìµå µ¥ÀÌÅͺ£À̽º µîÀÇ Á¾·ù·Î ºÐ·ùÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀϹÝÀûÀÎ µ¥ÀÌÅͺ£À̽º °ü¸® ½Ã½ºÅÛ(DBMS)¿¡´Â MySQL, Oracle, MongoDB µîÀÌ ÀÖÀ¸¸ç, µ¥ÀÌÅ͸¦ È¿À²ÀûÀ¸·Î °ü¸®Çϰí Á¶ÀÛÇϱâ À§ÇÑ ÅøÀ» Á¦°øÇϰí ÀÖ½À´Ï´Ù.

Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ äÅÃ

Ŭ¶ó¿ìµå ÄÄÇ»ÆÃÀ» äÅÃÇϸé È®À强, À¯¿¬¼º ¹× ºñ¿ë È¿À²¼ºÀÌ Çâ»óµÇ°í µ¥ÀÌÅͺ£À̽º ½ÃÀå¿¡ Å« ¿µÇâÀ» ¹ÌĨ´Ï´Ù. Ŭ¶ó¿ìµå µ¥ÀÌÅͺ£À̽º´Â ´ë±Ô¸ð ÀÎÇÁ¶ó ÅõÀÚ ¾øÀÌ °ß°íÇÑ ½ºÅ丮Áö¿Í °­·ÂÇÑ ÄÄÇ»ÆÃ ¸®¼Ò½º¿¡ ´ëÇÑ ½¬¿î Á¢±ÙÀ» ±â¾÷¿¡ Á¦°øÇÕ´Ï´Ù. ÀÚµ¿ ½ºÄÉÀϸµ, °í°¡¿ë¼º, º¸¾È µîÀÇ ±â´ÉÀ» °®Ãá Ŭ¶ó¿ìµå µ¥ÀÌÅͺ£À̽º´Â ±â¾÷ÀÌ ´ë·®ÀÇ µ¥ÀÌÅ͸¦ º¸´Ù È¿À²ÀûÀ¸·Î °ü¸®ÇÒ ¼ö ÀÖµµ·Ï ÇÕ´Ï´Ù. ÀÌ ½ÃÇÁÆ®´Â Çõ½ÅÀ» ÃËÁøÇÏ°í µ¥ÀÌÅÍ ÁÖµµÀÇ ÀÇ»ç°áÁ¤À» °¡¼ÓÈ­ÇÏ¸ç ´Ù¾çÇÑ ¾÷°è¿¡¼­ Ŭ¶ó¿ìµå ±â¹Ý µ¥ÀÌÅͺ£À̽º ¼Ö·ç¼ÇÀÇ ¼ºÀåÀ» µÞ¹ÞħÇϰí ÀÖ½À´Ï´Ù.

³ôÀº Ãʱâ ÅõÀÚ

µ¥ÀÌÅͺ£À̽º ½Ã½ºÅÛ¿¡ ´ëÇÑ °í¾×ÀÇ Ãʱâ ÅõÀÚ´Â Áß¼Ò±â¾÷°ú ½ÅÈï ±â¾÷ÀÇ Á¢±ÙÀ» Á¦ÇÑÇÏ¿© ½ÃÀå ¼ºÀåÀ» ¹æÇØÇÒ ¼ö ÀÖ½À´Ï´Ù. °í¾×ÀÇ Ãʱ⠺ñ¿ëÀÌ ÀáÀçÀûÀÎ µµÀÔÀÚÀÇ °É¸²µ¹ÀÌ µÇ¾î ¼±ÁøÀûÀÎ µ¥ÀÌÅͺ£À̽º ±â¼úÀÇ Ã¤¿ë·üÀÌ ÀúÇ쵃 °¡´É¼ºÀÌ ÀÖ½À´Ï´Ù. ¶ÇÇÑ ÀÌ·¯ÇÑ °æÁ¦Àû À庮Àº ±â¾÷ÀÌ Çõ½Å¿¡ ÇÒ¾ÖÇÏ´Â ÀÚ¿øÀÇ °¨¼Ò¸¦ ÇÇÇÒ ¼ö ¾ø°Ô ÇÏ¿© °æÀï·ÂÀÇ ´Ù¾ç¼ºÀ» ÀúÇϽÃŰ°í ½ÃÀå ÀüüÀÇ ÁøÈ­¸¦ µÐÈ­½Ãŵ´Ï´Ù. ±× °á°ú ½ÃÀåÀÇ ¼ºÀåÀº ÇÑÁ¤ÀûÀÌ µÇ¾î ±â¼úÀû Áøº¸µµ ÀúÇ쵃 °¡´É¼ºÀÌ ÀÖ½À´Ï´Ù.

½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸® ¼ö¿ä

½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸®¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡ÇÔ¿¡ µû¶ó µ¥ÀÌÅͺ£À̽º ½ÃÀå¿¡ Å« ¿µÇâÀ» ¹ÌÄ¡°í °í¼º´É, ³·Àº ´ë±â ½Ã°£ÀÇ µ¥ÀÌÅͺ£À̽º äÅÃÀ» ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ±â¾÷Àº °æÀï·ÂÀ» À¯ÁöÇϱâ À§ÇØ Áï°¢ÀûÀÎ ÀλçÀÌÆ®°¡ ÇÊ¿äÇϸç Àθ޸𸮠µ¥ÀÌÅͺ£À̽º, ½ºÆ®¸² ó¸®, NoSQL ¼Ö·ç¼Ç µîÀÇ ±â¼ú ¼ºÀåÀ¸·Î À̾îÁö°í ÀÖ½À´Ï´Ù. ÀÌ ½ÃÇÁÆ®´Â ¾÷¹« È¿À²À» ³ôÀ̰í ÀÇ»ç °áÁ¤À» °¡¼ÓÈ­ÇÏ¿© ´õ ³ªÀº °í°´ °æÇèÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù. ±â¾÷ÀÌ ½Ç½Ã°£ ºÐ¼®À» ¿ì¼±½ÃÇÏ´Â °¡¿îµ¥, µ¥ÀÌÅͺ£À̽º ÇÁ·Î¹ÙÀÌ´õ´Â º¸´Ù È®Àå °¡´ÉÇϰí À¯¿¬ÇÏ¸ç °ß°íÇÑ ¼Ö·ç¼ÇÀ» Á¦°øÇϱâ À§ÇØ ±â¼ú Çõ½ÅÀ» ÁøÇàÇÏ°í ½ÃÀå Á¤¼¼¸¦ À籸ÃàÇϰí ÀÖ½À´Ï´Ù.

°ü¸® º¹À⼺

µ¥ÀÌÅͺ£À̽º °ü¸®ÀÇ º¹À⼺Àº ¿î¿µ ºñ¿ë°ú ¸®¼Ò½º ¼ö¿ä¸¦ Áõ°¡½ÃŰ°í ½ÃÀå ¼ºÀåÀ» ¹æÇØÇÒ ¼ö ÀÖ½À´Ï´Ù. µ¥ÀÌÅͺ£À̽º°¡ ´ë±Ô¸ðÈ­, º¹ÀâÈ­µÊ¿¡ µû¶ó ±â¾÷Àº µ¥ÀÌÅÍ ÅëÇÕ, º¸¾È, È®À强 °úÁ¦¿¡ Á÷¸éÇÕ´Ï´Ù. ÀÌ·¯ÇÑ º¹À⼺Àº À¯Áöº¸¼ö ¿ä°ÇÀÇ Áõ°¡, ±¸Çö ÀÏÁ¤ÀÇ Àå±âÈ­, Àü¹® ±â¼úÀÇ Çʿ伺À¸·Î À̾îÁ® Á¶Á÷ÀÌ ½ÃÀåÀÇ ¼ö¿ä¿¡ ½Å¼ÓÇÏ°Ô ÀûÀÀÇÏ´Â °ÍÀ» ¾î·Æ°Ô ÇÕ´Ï´Ù. ÀÌ·¯ÇÑ À庮Àº Çõ½ÅÀ» Áö¿¬½ÃŰ°í ½Å±Ô µµÀÔÀÇ ÀÇ¿åÀ» ÀúÇϽÃŵ´Ï´Ù.

COVID-19ÀÇ ¿µÇâ

COVID-19ÀÇ À¯ÇàÀº ºñÁî´Ï½ºÀÇ ¿ø°ÝÁö·ÎÀÇ À̵¿¿¡ µû¶ó Ŭ¶ó¿ìµå ±â¹Ý µ¥ÀÌÅͺ£À̽ºÀÇ Ã¤¿ëÀ» Å©°Ô °¡¼ÓÈ­Çß½À´Ï´Ù. µðÁöÅÐ ¼­ºñ½º¿¡ ´ëÇÑ ÀÇÁ¸µµ°¡ ³ô¾ÆÁö¸é¼­ È®À强 ÀÖ°í ¾ÈÀüÇϸç Á¢±ÙÇϱ⠽¬¿î µ¥ÀÌÅͺ£À̽º ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä°¡ ³ô¾ÆÁ³½À´Ï´Ù. ÀüÀÚ»ó°Å·¡, ¿ø°Ý±Ù¹«, ¿Â¶óÀÎ ¼­ºñ½ºÀÇ ±ÞÁõµµ ÀÚµ¿È­, ½Ç½Ã°£ ºÐ¼®, µ¥ÀÌÅÍ º¸¾È °­È­¿¡ ÃÊÁ¡À» ¸ÂÃá ½ÃÀåÀÇ ¼ºÀåÀ» µÞ¹ÞħÇß½À´Ï´Ù. ÀÌ º¯ÇõÀº µ¥ÀÌÅͺ£À̽º ½ÃÀåÀ» ÀçÇü¼ºÇÏ¿© º¸´Ù Çõ½ÅÀûÀ̰í À¯¿¬ÇÑ ½ÃÀåÀ¸·Î ²ø¾î¿Ã¸®°í ÀÖ½À´Ï´Ù.

¿¹Ãø ±â°£ µ¿¾È NewSQL µ¥ÀÌÅͺ£À̽º ºÎ¹®ÀÌ ÃÖ´ë°¡ µÉ °ÍÀ¸·Î ¿¹»ó

NewSQL µ¥ÀÌÅͺ£À̽º ºÎ¹®Àº ¿¹Ãø ±â°£ µ¿¾È °¡Àå Å« ½ÃÀå Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÌ´Â ÀÌ ±â¼ú Çõ½ÅÀÌ ¼º´É Çâ»óÀ» ÃËÁøÇÏ°í ±â¾÷ÀÌ µ¥ÀÌÅÍ ¹«°á¼ºÀ» À¯ÁöÇϸ鼭 ´ë±Ô¸ð·Î °Å·¡·®ÀÌ ¸¹Àº ¿öÅ©·Îµå¸¦ °ü¸®ÇÒ ¼ö ÀÖµµ·Ï Çϱâ À§ÇÔÀÔ´Ï´Ù. NewSQL µ¥ÀÌÅͺ£À̽º´Â ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸®¸¦ ÇÊ¿ä·Î ÇÏ´Â ÃֽоÖÇø®ÄÉÀ̼ÇÀ» Áö¿øÇÏ¸ç ±ÝÀ¶, ÀüÀÚ»ó°Å·¡, IoT µî ¾÷°è ¼ºÀå¿¡ ¹ÚÂ÷¸¦ °¡Çϰí ÀÖ½À´Ï´Ù. º¹ÀâÇÏ°í ¹Ì¼Ç Å©¸®Æ¼ÄÃÇÑ ¾ÖÇø®ÄÉÀ̼ÇÀ» ó¸®ÇÏ´Â ±× ´É·ÂÀº ÁøÈ­ÇÏ´Â µ¥ÀÌÅͺ£À̽º ¾÷°è¿¡¼­ °­·ÂÇÑ ÈûÀÌ µÇ°í ÀÖ½À´Ï´Ù.

¿¹Ãø ±â°£ µ¿¾È ÄÁÅÙÃ÷ °ü¸® ºÐ¾ßÀÇ CAGRÀÌ °¡Àå ³ô¾ÆÁú Àü¸Á

¿¹Ãø ±â°£ µ¿¾È ÄÁÅÙÃ÷ °ü¸® ºÐ¾ß°¡ °¡Àå ³ôÀº ¼ºÀå·üÀ» º¸ÀÏ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. Á¶Á÷ÀÌ ÄÜÅÙÃ÷ °ü¸® ½Ã½ºÅÛ(CMS)À» äÅÃÇÏ´Â °æÇâÀÌ °­ÇØÁü¿¡ µû¶ó ´ë±Ô¸ð·Î ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸®¸¦ Áö¿øÇÏ´Â °ß°íÇÑ µ¥ÀÌÅͺ£À̽º¿¡ ´ëÇÑ ¼ö¿ä°¡ ³ô¾ÆÁý´Ï´Ù. ÀÌ ÅëÇÕ¿¡ ÀÇÇØ µ¥ÀÌÅÍ¿¡ ´ëÇÑ Á¢±Ù¼º, º¸¾È, È®À强ÀÌ Çâ»óµÇ¾î ´Ù¾çÇÑ ÄÜÅÙÃ÷¸¦ ´Ù·ç´Â ºñÁî´Ï½º¿¡ ÇʼöÀûÀÎ °ÍÀÌ µË´Ï´Ù. ±× °á°ú, ÄÁÅÙÃ÷ °ü¸® ºÎ¹®Àº ±â¼ú Çõ½ÅÀ» °¡¼ÓÇØ, ½ÃÀå È®´ë¿¡ ¹ÚÂ÷¸¦ °¡ÇÏ´Â °Í°ú µ¿½Ã¿¡, ÁøÈ­ÇÏ´Â µðÁöÅÐ ÀüȯÀÇ ¿ä±¸¿¡ ´ëÀÀÇÏ´Â µ¥ÀÌÅͺ£À̽º ±â¼úÀ» °­È­Çϰí ÀÖ½À´Ï´Ù.

ÃÖ´ë Á¡À¯À²À» Â÷ÁöÇÏ´Â Áö¿ª

¿¹Ãø ±â°£ µ¿¾È ¾Æ½Ã¾ÆÅÂÆò¾çÀº µðÁöÅÐ Àüȯ Áõ°¡, µ¥ÀÌÅÍ Áß½ÉÀÇ ÀÇ»ç °áÁ¤, Ŭ¶ó¿ìµå ÄÄÇ»ÆÃÀÇ µîÀåÀ¸·Î ÃÖ´ë ½ÃÀå Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ¾÷°è¸¦ ºÒ¹®ÇÏ°í ±â¾÷Àº µ¥ÀÌÅÍ °ü¸®, È®À强, º¸¾ÈÀ» °­È­Çϱâ À§ÇØ ¼±ÁøÀûÀÎ µ¥ÀÌÅͺ£À̽º ¼Ö·ç¼ÇÀ» äÅÃÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ¼ºÀåÀÇ ¿øµ¿·ÂÀÌ µÇ°í ÀÖ´Â °ÍÀº ½Ç½Ã°£ ºÐ¼®, ÀΰøÁö´É, ¹æ´ëÇÑ µ¥ÀÌÅÍ °ü¸®ÀÇ Çʿ伺¿¡ ´ëÇÑ ¼ö¿äÀÇ Áõ°¡ÀÔ´Ï´Ù. ±× °á°ú, ÀÌ ½ÃÀåÀº Çõ½ÅÀ» ÃËÁøÇØ, ¾÷¹« È¿À²À» Çâ»ó½Ã۰í, ÀÌ Áö¿ªÀÇ °æÁ¦ °³Ã´¿¡ °øÇåÇϰí ÀÖ½À´Ï´Ù.

CAGRÀÌ °¡Àå ³ôÀº Áö¿ª :

¿¹Ãø ±â°£ µ¿¾È ºÏ¹Ì´Â µ¥ÀÌÅÍ °ü¸®, Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ ¹× °íµµ ºÐ¼® ¼ö¿ä·Î ÀÎÇØ °¡Àå ³ôÀº CAGRÀ» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ±â¾÷Àº ¾÷¹« È¿À², ÀÇ»ç °áÁ¤, °í°´ °æÇèÀ» °­È­Çϱâ À§ÇØ Çõ½ÅÀûÀÎ µ¥ÀÌÅͺ£À̽º ¼Ö·ç¼ÇÀ» äÅÃÇϰí ÀÖ½À´Ï´Ù. AI, IoT, ºòµ¥ÀÌÅÍÀÇ ´ëµÎ·Î ½ÃÀåÀº ºü¸£°Ô ÁøÈ­Çϰí ÀÖÀ¸¸ç ÇコÄɾî, ±ÝÀ¶, ¼Ò¸Å µîÀÇ ºÐ¾ß¿¡ »õ·Î¿î ±âȸ¸¦ Á¦°øÇϰí ÀÖ½À´Ï´Ù. ÀÌ º¯ÇõÀº °æÁ¦¼ºÀåÀ» ÃËÁøÇϰí, °í¿ëÀ» âÃâÇØ, ºÏ¹Ì¸¦ ¼¼°è ¹× µ¥ÀÌÅÍ °æÁ¦ÀÇ ¸®´õ·Î¼­ Æò°¡Çϰí ÀÖ½À´Ï´Ù.

¹«·á ¸ÂÃãÇü ¼­ºñ½º

ÀÌ º¸°í¼­¸¦ ±¸µ¶ÇÏ´Â °í°´Àº ´ÙÀ½ ¹«·á ¸ÂÃã¼³Á¤ ¿É¼Ç Áß Çϳª¸¦ »ç¿ëÇÒ ¼ö ÀÖ½À´Ï´Ù.

  • ±â¾÷ ÇÁ·ÎÆÄÀÏ
    • Ãß°¡ ±â¾÷ÀÇ Á¾ÇÕÀû ÇÁ·ÎÆÄÀϸµ(3°³»ç±îÁö)
    • ÁÖ¿ä ±â¾÷ÀÇ SWOT ºÐ¼®(3°³»ç±îÁö)
  • Áö¿ª ±¸ºÐ
    • °í°´ÀÇ °ü½É¿¡ ÀÀÇÑ ÁÖ¿ä±¹ ½ÃÀå Ãß°è, ¿¹Ãø ¹× CAGR(ÁÖ : Ÿ´ç¼º È®Àο¡ µû¸§)
  • °æÀï º¥Ä¡¸¶Å·
    • Á¦Ç° Æ÷Æ®Æú¸®¿À, Áö¸®Àû Á¸Àç, Àü·«Àû Á¦ÈÞ¿¡ ±â¹ÝÇÑ ÁÖ¿ä ±â¾÷ º¥Ä¡¸¶Å·

¸ñÂ÷

Á¦1Àå ÁÖ¿ä ¿ä¾à

Á¦2Àå ¼­·Ð

  • °³¿ä
  • ÀÌÇØ°ü°èÀÚ
  • ºÐ¼® ¹üÀ§
  • ºÐ¼® ¹æ¹ý
    • µ¥ÀÌÅÍ ¸¶ÀÌ´×
    • µ¥ÀÌÅÍ ºÐ¼®
    • µ¥ÀÌÅÍ °ËÁõ
    • ºÐ¼® Á¢±Ù
  • ºÐ¼® ÀÚ·á
    • 1Â÷ Á¶»ç ÀÚ·á
    • 2Â÷ Á¶»ç Á¤º¸¿ø
    • ÀüÁ¦Á¶°Ç

Á¦3Àå ½ÃÀå µ¿Ç⠺м®

  • ¼­¹®
  • ¼ºÀå ÃËÁø¿äÀÎ
  • ¼ºÀå ¾ïÁ¦¿äÀÎ
  • ½ÃÀå ±âȸ
  • À§Çù
  • ¿ëµµ ºÐ¼®
  • ÃÖÁ¾ »ç¿ëÀÚ ºÐ¼®
  • ½ÅÈï ½ÃÀå
  • ½ÅÇü Äڷγª ¹ÙÀÌ·¯½º °¨¿°(COVID-19)ÀÇ ¿µÇâ

Á¦4Àå Porter's Five Forces ºÐ¼®

  • °ø±ÞÀÚÀÇ Çù»ó·Â
  • ¹ÙÀ̾îÀÇ Çù»ó·Â
  • ´ëü Á¦Ç°ÀÇ À§Çù
  • ½Å±Ô ÁøÃâ±â¾÷ÀÇ À§Çù
  • ±â¾÷°£ °æÀï

Á¦5Àå ¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀå : µ¥ÀÌÅͺ£À̽º À¯Çüº°

  • °ü°èÇü µ¥ÀÌÅͺ£À̽º(RDBMS)
  • ºñ°ü°è ¹× NoSQL µ¥ÀÌÅͺ£À̽º
    • ¹®¼­ ½ºÅä¾î
    • Ű ¹ë·ù ½ºÅä¾î
    • Ä÷³ ½ºÅä¾î
  • NewSQL µ¥ÀÌÅͺ£À̽º
  • ½Ã°è¿­ µ¥ÀÌÅͺ£À̽º
  • Àθ޸𸮠µ¥ÀÌÅͺ£À̽º
  • ¿ÀºêÁ§Æ® ÁöÇâ µ¥ÀÌÅͺ£À̽º

Á¦6Àå ¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀå : Àü°³ ¹æ½Ä

  • ¿ÂÇÁ·¹¹Ì½º
  • Ŭ¶ó¿ìµå ±â¹Ý

Á¦7Àå ¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀå : Á¶Á÷ ±Ô¸ðº°

  • Áß¼Ò±â¾÷
  • ´ë±â¾÷

Á¦8Àå ¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀå : ¿ëµµº°

  • µ¥ÀÌÅÍ ¿þ¾îÇϿ콺
  • °í°´ °ü°è °ü¸®(CRM)
  • ±â¾÷ ÀÚ¿ø °èȹ(ERP)
  • ºñÁî´Ï½º ÀÎÅÚ¸®Àü½º(BI)
  • ÄÁÅÙÃ÷ °ü¸®
  • °ø±Þ¸Á °ü¸®(SCM)
  • ±âŸ ¿ëµµ

Á¦9Àå ¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀå : ÃÖÁ¾ »ç¿ëÀÚº°

  • ÀºÇà ¹× ±ÝÀ¶ ¼­ºñ½º, º¸Çè(BFSI)
  • IT ¹× Åë½Å
  • ÀÇ·á ¹× »ý¸í°úÇÐ
  • ¼Ò¸Å¾÷ ¹× ÀüÀÚ»ó°Å·¡
  • Á¦Á¶¾÷
  • Á¤ºÎ ¹× °ø°ø ºÎ¹®
  • ¹Ìµð¾î ¹× ¿£ÅÍÅ×ÀÎ¸ÕÆ®
  • ¿î¼Û ¹× ¹°·ù
  • ¿¡³ÊÁö ¹× À¯Æ¿¸®Æ¼
  • ±³À°
  • ±âŸ ÃÖÁ¾ »ç¿ëÀÚ

Á¦10Àå ¼¼°èÀÇ µ¥ÀÌÅͺ£À̽º ½ÃÀå : Áö¿ªº°

  • ºÏ¹Ì
    • ¹Ì±¹
    • ij³ª´Ù
    • ¸ß½ÃÄÚ
  • À¯·´
    • µ¶ÀÏ
    • ¿µ±¹
    • ÀÌÅ»¸®¾Æ
    • ÇÁ¶û½º
    • ½ºÆäÀÎ
    • ±âŸ À¯·´
  • ¾Æ½Ã¾ÆÅÂÆò¾ç
    • ÀϺ»
    • Áß±¹
    • Àεµ
    • È£ÁÖ
    • ´ºÁú·£µå
    • Çѱ¹
    • ±âŸ ¾Æ½Ã¾ÆÅÂÆò¾ç
  • ³²¹Ì
    • ¾Æ¸£ÇîÆ¼³ª
    • ºê¶óÁú
    • Ä¥·¹
    • ±âŸ ³²¹Ì
  • Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«
    • »ç¿ìµð¾Æ¶óºñ¾Æ
    • ¾Æ¶ø¿¡¹Ì¸®Æ®(UAE)
    • īŸ¸£
    • ³²¾ÆÇÁ¸®Ä«
    • ±âŸ Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«

Á¦11Àå ÁÖ¿ä µ¿Çâ

  • °è¾à, »ç¾÷ Á¦ÈÞ ¹× Çù·Â, ÇÕÀÛ »ç¾÷
  • ±â¾÷ ÇÕº´ ¹× Àμö(M&A)
  • ½ÅÁ¦Ç° ¹ß¸Å
  • È®Àå
  • ±âŸ ÁÖ¿ä Àü·«

Á¦12Àå ±â¾÷ ÇÁ·ÎÆÄÀϸµ

  • Oracle
  • Microsoft
  • IBM
  • SAP
  • Teradata
  • Amazon Web Services(AWS)
  • Google Cloud
  • Snowflake
  • MongoDB
  • Couchbase
  • DataStax
  • Redis
  • Neo4j
  • Cockroach Labs
  • MariaDB
  • Cloudera
  • InfluxData
  • Timescale
  • Rockset
  • SingleStore
AJY

According to Stratistics MRC, the Global Database Market is accounted for $150.3 billion in 2025 and is expected to reach $429.9 billion by 2032 growing at a CAGR of 16.2% during the forecast period. A database is an organized collection of structured information or data stored electronically in a system. It is designed to efficiently store, manage, and retrieve data, often in the form of tables, records, and fields. Databases are used to handle large volumes of data, ensuring accuracy, security, and accessibility. They support various operations like data insertion, deletion, updating, and querying. Modern databases can be categorized into types such as relational, non-relational, distributed, and cloud databases. Popular database management systems (DBMS) include MySQL, Oracle, and MongoDB, which provide tools for managing and manipulating data effectively.

Market Dynamics:

Driver:

Cloud Computing Adoption

The adoption of cloud computing has significantly impacted the database market by enabling greater scalability, flexibility, and cost-efficiency. Cloud databases offer businesses easy access to robust storage and powerful computing resources without the need for extensive infrastructure investments. With features like automatic scaling, high availability, and security, cloud databases empower organizations to manage large volumes of data more effectively. This shift promotes innovation, accelerates data-driven decision-making, and drives the growth of cloud-based database solutions in various industries.

Restraint:

High Initial Investment

High initial investment in database systems can hinder market growth by limiting accessibility for smaller businesses and startups. The significant upfront costs may deter potential adopters, leading to a slower adoption rate of advanced database technologies. This financial barrier also forces companies to allocate fewer resources for innovation, reducing competitive diversity and slowing overall market evolution. As a result, the market may experience limited growth and reduced technological advancement.

Opportunity:

Demand for Real-Time Data Processing

The increasing demand for real-time data processing is significantly impacting the database market, driving the adoption of high-performance, low-latency databases. Organizations require instant insights to remain competitive, leading to growth in technologies like in-memory databases, stream processing, and NoSQL solutions. This shift enhances operational efficiency, accelerates decision-making, and enables better customer experiences. As businesses prioritize real-time analytics, database providers innovate to offer more scalable, flexible, and robust solutions, reshaping the market landscape.

Threat:

Complexity in Management

The complexity in management of databases can hinder market growth by increasing operational costs and resource demands. As databases grow larger and more intricate, businesses face challenges in data integration, security, and scalability. This complexity leads to higher maintenance requirements, longer implementation timelines, and the need for specialized skills, making it difficult for organizations to quickly adapt to market demands. Such barriers can slow innovation and discourage new adopters.

Covid-19 Impact

The COVID-19 pandemic significantly accelerated the adoption of cloud-based databases as businesses shifted to remote operations. Increased reliance on digital services drove demand for scalable, secure, and accessible database solutions. The surge in e-commerce, remote work, and online services also fueled market growth, with a focus on automation, real-time analytics, and enhanced data security. This transformation has reshaped the database market, pushing for more innovation and flexibility.

The NewSQL databases segment is expected to be the largest during the forecast period

The NewSQL databases segment is expected to account for the largest market share during the forecast period, because this innovation drives performance improvements, enabling enterprises to manage large-scale, high-transaction workloads while maintaining strong data integrity. NewSQL databases support modern applications requiring real-time data processing, fueling growth in industries like finance, e-commerce, and IoT. Their ability to handle complex, mission-critical applications positions them as a powerful force in the evolving database landscape.

The content management segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the content management segment is predicted to witness the highest growth rate, as organizations increasingly adopt content management systems (CMS), the demand for robust databases rises to support large-scale, real-time data processing. This integration fosters improved data accessibility, security, and scalability, which are crucial for businesses handling diverse content types. Consequently, the content management sector accelerates innovation, fueling market expansion, and enhancing database technologies to meet evolving digital transformation needs.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to increasing digital transformation, data-driven decision-making, and the rise of cloud computing. Businesses across industries are adopting advanced database solutions to enhance data management, scalability, and security. This growth is fueled by the increasing demand for real-time analytics, artificial intelligence, and the need to manage vast amounts of data. As a result, the market is fostering innovation, improving operational efficiencies, and contributing to economic development in the region.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to demand for data management, cloud computing, and advanced analytics. Businesses are adopting innovative database solutions to enhance operational efficiency, decision-making, and customer experiences. With the rise of AI, IoT, and big data, the market is evolving rapidly, offering new opportunities in sectors like healthcare, finance, and retail. This transformation is fueling economic growth, creating jobs, and positioning North America as a leader in the global data economy.

Key players in the market

Some of the key players profiled in the Database Market include Oracle, Microsoft, IBM, SAP, Teradata, Amazon Web Services (AWS), Google Cloud, Snowflake, MongoDB, Couchbase, DataStax, Redis, Neo4j, Cockroach Labs, MariaDB, Cloudera, InfluxData, Timescale, Rockset and SingleStore.

Key Developments:

In January 2025, Microsoft announced an evolution of its strategic partnership with OpenAI, aiming to propel the next phase of artificial intelligence (AI) innovation. This extended collaboration builds upon their 2019 agreement, reinforcing their commitment to advancing AI technologies responsibly and effectively.

In April 2024, Cloud Software Group and Microsoft have entered into an eight-year strategic partnership aimed at delivering joint cloud solutions and generative AI technologies to over 100 million users worldwide. This collaboration is particularly significant in the context of enterprise desktop services, with Citrix, a business unit of Cloud Software Group, being designated as Microsoft's preferred Global Azure Partner for Enterprise Desktop as a Service.

Database Types Covered:

  • Relational Databases (RDBMS)
  • Non-relational / NoSQL Databases
  • NewSQL Databases
  • Time-Series Databases
  • In-memory Databases
  • Object-oriented Databases

Deployment Modes Covered:

  • On-premises
  • Cloud-based

Organization Sizes Covered:

  • Small and Medium Enterprises (SMEs)
  • Large Enterprises

Applications Covered:

  • Data Warehousing
  • Customer Relationship Management (CRM)
  • Enterprise Resource Planning (ERP)
  • Business Intelligence (BI)
  • Content Management
  • Supply Chain Management (SCM)
  • Other Applications

End Users Covered:

  • Banking, Financial Services, and Insurance (BFSI)
  • IT and Telecommunications
  • Healthcare and Life Sciences
  • Retail and E-commerce
  • Manufacturing
  • Government and Public Sector
  • Media and Entertainment
  • Transportation and Logistics
  • Energy and Utilities
  • Education
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Database Market, By Database Type

  • 5.1 Introduction
  • 5.2 Relational Databases (RDBMS)
  • 5.3 Non-relational / NoSQL Databases
    • 5.3.1 Document Stores
    • 5.3.2 Key-Value Stores
    • 5.3.3 Columnar Stores
  • 5.4 NewSQL Databases
  • 5.5 Time-Series Databases
  • 5.6 In-memory Databases
  • 5.7 Object-oriented Databases

6 Global Database Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 On-premises
  • 6.3 Cloud-based

7 Global Database Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Small and Medium Enterprises (SMEs)
  • 7.3 Large Enterprises

8 Global Database Market, By Application

  • 8.1 Introduction
  • 8.2 Data Warehousing
  • 8.3 Customer Relationship Management (CRM)
  • 8.4 Enterprise Resource Planning (ERP)
  • 8.5 Business Intelligence (BI)
  • 8.6 Content Management
  • 8.7 Supply Chain Management (SCM)
  • 8.8 Other Applications

9 Global Database Market, By End User

  • 9.1 Introduction
  • 9.2 Banking, Financial Services, and Insurance (BFSI)
  • 9.3 IT and Telecommunications
  • 9.4 Healthcare and Life Sciences
  • 9.5 Retail and E-commerce
  • 9.6 Manufacturing
  • 9.7 Government and Public Sector
  • 9.8 Media and Entertainment
  • 9.9 Transportation and Logistics
  • 9.10 Energy and Utilities
  • 9.11 Education
  • 9.12 Other End Users

10 Global Database Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Oracle
  • 12.2 Microsoft
  • 12.3 IBM
  • 12.4 SAP
  • 12.5 Teradata
  • 12.6 Amazon Web Services (AWS)
  • 12.7 Google Cloud
  • 12.8 Snowflake
  • 12.9 MongoDB
  • 12.10 Couchbase
  • 12.11 DataStax
  • 12.12 Redis
  • 12.13 Neo4j
  • 12.14 Cockroach Labs
  • 12.15 MariaDB
  • 12.16 Cloudera
  • 12.17 InfluxData
  • 12.18 Timescale
  • 12.19 Rockset
  • 12.20 SingleStore
»ùÇà ¿äû ¸ñ·Ï
0 °ÇÀÇ »óǰÀ» ¼±Åà Áß
¸ñ·Ï º¸±â
Àüü»èÁ¦