https://slideship.com/users/@marcy-terui/presentations/2017/11/NV8cP63mxs1tLw4qkct7Xd/
NoSQLã®æˆåŠŸã¯1:10å•é¡Œã«ã‹ã‹ã£ã¦ã„ã‚‹:Kenn's Clairvoyance
ã“ã“2-3å¹´ã»ã©ã€ã„ã‚ゆるéžSQL系データベースãŒãƒ›ãƒƒãƒˆãªè©±é¡Œã«ãªã£ã¦ãã¦ã„ã¾ã™ã€‚ã“ã®ãƒ ーブメントをç·ç§°ã—ã¦ã€ŒNoSQL (Not-only SQL)ã€ã¨å‘¼ã°ã‚Œã‚‹ã“ã¨ãŒå¤šã„よã†ã§ã™ã€‚ã¾ã‚‹ã§SQLã‚’å¦å®šã—ã¦ã„ã‚‹ã‹ã®ã‚ˆã†ãªèª¤è§£ã‚’æ‹›ãã‚„ã™ã„用語ã§ã™ãŒã€ã‹ã¨ã„ã£ã¦ã‚ー・ãƒãƒªãƒ¥ãƒ¼åž‹ãƒ‡ãƒ¼ã‚¿ã‚¹ãƒˆã‚¢ã‚„列指å‘DBã‚’ç·ç§°ã§ãã‚‹ä»–ã®å‘¼ã³æ–¹ã‚‚ãªã„ã®ã§ã€ã“ã®ã‚¨ãƒ³ãƒˆãƒªã§ã¯NoSQLã¨ã„ã†ç”¨èªžã‚’使ã†ã“ã¨ã«ã—ã¾ã™ã€‚ Oracleã‚„MySQLãªã©ã®SQLデータベースãŒæˆç†Ÿã—ã¦ã„ã一方ã§ã€SQLデータベースを特徴ã¥ã‘る弱点ã§ã‚る柔軟性ã®ãªã•ã€å …牢ã•ã¨å¼•ãæ›ãˆã«çŠ 牲ã«ãªã£ãŸæ›´æ–°æ€§èƒ½ã®ä½Žã•ã€ã‚¹ã‚±ãƒ¼ãƒ«ã‚¢ã‚¦ãƒˆã®é›£ã—ã•ãªã©ã‹ã‚‰ã€ã€Œä½•ã§ã‚‚ã‹ã‚“ã§ã‚‚RDBã€ã‹ã‚‰ã€Œç›®çš„ã«å¿œã˜ãŸæ°¸ç¶šåŒ–ã€ãŒæ¨¡ç´¢ã•ã‚Œã‚‹æµã‚Œã«ãªã£ã¦ãã¾ã—ãŸã€‚ 時をåŒã˜ãã—ã¦ã€ã‚ャッシュサーãƒã®ä¸–ç•Œã§ã‚‚ã€Memcachedã®ã‚‚ã¤ã‚·ãƒ³ãƒ—ルãªAPIã®ä½¿ã„ã‚„ã™ã•ãŒè©•ä¾¡ã•ã‚Œã‚‹ä¸€æ–¹ã€LRUã«ã‚ˆ
NoSQLを知る
The document contains charts and graphs showing performance test results for different key-value store systems. A line graph shows the number of requests per second for Viver, Runes and V-Field systems with varying request sizes. Another set of line graphs show the latency percentage for different request sizes on two systems. The document also includes URLs and diagrams showing the architecture o
NOSQL Patterns
Over the last couple years, we see an emerging data storage mechanism for storing large scale of data. These storage solution differs quite significantly with the RDBMS model and is also known as the NOSQL. Some of the key players include ... GoogleBigTable, HBase, Hypertable AmazonDynamo, Voldemort, Cassendra, Riak Redis CouchDB, MongoDB These solutions has a number of characteristics in common K
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http://www.shudo.net/publications/NoSQL-data-model-200912/
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