[B! nosql] masa_wã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

masa_w id:masa_w

nosqlã«é–¢ã™ã‚‹masa_wã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (22)

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ç‘æ³¢å¤§å¦ã§ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã®è©±ã‚’ã—ã¦ãã¾ã—ãŸ - kuenishi's blog
ç‘æ³¢å¤§å¦ã®å·å³¶å…ˆç”Ÿã«å‘¼ã°ã‚Œã¦æœ¨ã€é‡‘ã¨æƒ…å ±ã‚·ã‚¹ãƒ†ãƒ ç‰¹åˆ¥è¬›ç¾©Dã¨ã„ã†ã‚„ã¤ã«å‚åŠ ã—ã¦ããŸã€‚ã“ã‚“ãªã“ã¨ã«ãªã‚‹ã¨ã¯æ€ã£ã¦ã„ãªã‹ã£ãŸãŒã€ã‚ã‚ã†ã“ã¨ã‹è¬›å¸«å´ã§å‘¼ã°ã‚Œã¦ã—ã¾ã„ã€æ€ãˆã°é ãã¸æ¥ãŸã‚‚ã®ã ã¨æ„Ÿæ…¨æ·±ã„ã€‚ãƒ•ãƒªã¯ã€ŒRiakã¨NoSQLã®è©±ã‚’ã—ã¦ã‚‚ã‚‰ãˆãŸã‚‰ã€ã¨ã„ã†éžå¸¸ã«è‡ªç”±åº¦ã®é«˜ã„å†…å®¹ãªã®ã§ã€ã›ã£ã‹ããªã®ã§åƒ•ã®çŸ¥ã£ã¦ã„ã‚‹ã“ã¨ã‚’å…¨éƒ¨è©°ã‚è¾¼ã‚“ã§è©±ã—ã¦ã‚„ã‚ã†ã¨æ€ã£ãŸã‚‰10åˆ†å»¶é•·ã—ã¦ã•ã‚‰ã«ã‚¹ãƒ©ã‚¤ãƒ‰10æžšåˆ†ãã‚‰ã„ã‚’æ¶ˆåŒ–ä¸è‰¯ã§çµ‚äº†ã¨ã„ã†ã€ã¿ã£ã¨ã‚‚ãªã„æ„Ÿã˜ã«ãªã£ã¦ã—ã¾ã£ãŸã€‚ã‹ãªã‚Šç«¯æŠ˜ã£ã¦ãƒã‚¤ãƒ³ãƒˆã ã‘èª¬æ˜Žã—ãŸã®ã§æµã‚ŒãŒåˆ†ã‹ã‚‰ãšè‹¦åŠ´ã—ãŸæ–¹ã‚‚å¤šã„ã¨æ€ã†ãŒã€ã¾ã‚åƒ•ã®æ€§æ ¼ãªã®ã§è¨±ã—ã¦ã»ã—ã„ã€‚ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã®è¬›ç¾©ã‚’ã²ã¨é€šã‚Šçµ‚ãˆãŸé™¢ç”Ÿãƒ¬ãƒ™ãƒ«ã‚’æƒ³å®šã—ã¦ã‚¹ãƒ©ã‚¤ãƒ‰ã‚’ä½œã£ãŸã®ã§ã€ã‚‚ã—ã‹ã™ã‚‹ã¨ã€ã‚ã‚Šã¨é›£ã—ã‹ã£ãŸã‚Šåˆ†ã‹ã‚Šã«ãã‹ã£ãŸã‚Šã™ã‚‹ã‹ã‚‚ã—ã‚Œãªã„ã®ã§ã€ã‚ã‹ã‚‰ãªã„ã“ã¨ãŒã‚ã£ãŸã‚‰é©å½“ã«è³ªå•ã—ã¦ãã ã•ã„ã€‚ è¨€ã„ãŸã‹ã£ãŸã“ã¨ã®æµã‚Œã‚’åƒ•ãªã‚Šã«ã¾ã¨ã‚ã‚‹ã¨
masa_w 2014/02/02
nosql

riak

DB
ãƒªãƒ³ã‚¯
CyberAgentã«ãŠã‘ã‚‹MongoDB
2. ã‚¢ã‚¸ã‚§ãƒ³ãƒ€ nï® Amebaã®ã‚µãƒ¼ãƒ“ã‚¹ nï® ã‚µãƒ¼ãƒ“ã‚¹ç’°å¢ƒã®å¤‰é· nï® ã‚µãƒ¼ãƒ“ã‚¹ã‚’æ”¯ãˆã‚‹Mongo DB nï® å›°ã£ãŸã“ã¨ãªã© nï® é‹ç”¨ã«ã¤ã„ã¦ nï® ã¾ã¨ã‚ 13å¹´12æœˆ12æ—¥æœ¨æ›œæ—¥ 3. è‡ªå·±ç´¹ä»‹ nï® æ¡‘é‡Žç« å¼˜ lï¬ ã‚µã‚¤ãƒãƒ¼ã‚¨ãƒ¼ã‚¸ã‚§ãƒ³ãƒˆ lï¬ Ameba ã‚’é‹å–¶ã—ã¦ã„ã¾ã™ã€‚ lï¬ ãƒ”ã‚°ã‚½ãƒ¼ã‚·ãƒ£ãƒ«ã‚²ãƒ¼ãƒ ã®é‹ç”¨ï¼æ§‹ç¯‰ã‚’æ‹…å½“ lï¬ Twitter lï¬ @kuwa_tw lï¬ Blog lï¬ http://d.hatena.ne.jp/akuwano/ 13å¹´12æœˆ12æ—¥æœ¨æ›œæ—¥
masa_w 2013/12/13
MongoDB

nosql
ãƒªãƒ³ã‚¯
NoSQL and Full Text Indexing: Two Trends
masa_w 2013/05/27
nosql

MongoDB

Riak
ãƒªãƒ³ã‚¯
mongodbã®ãƒ‡ã‚£ã‚¹ã‚¯é ˜åŸŸã‚’è§£æ”¾ã™ã‚‹ã®ãŒé›£ã—ã„å•é¡Œ
Issei Naruta @mirakui mongo dbã€ãƒ‡ã‚£ã‚¹ã‚¯å®¹é‡ã‚’ç©ºã‘ã‚‹ãŸã‚ã« db.repairDatabase() ã—ãŸã‚‰ãƒ‡ã‚£ã‚¹ã‚¯å®¹é‡ãŒè¶³ã‚Šãªã„ã£ã¦è¨€ã‚ã‚Œã‚‹ã—ã€æœã‚’è²·ã„ã«è¡ŒãæœãŒç„¡ã„çŠ¶æ…‹ã«ãªã‚‹ 2012-10-16 18:52:59
masa_w 2013/04/24
MongoDB

nosql
ãƒªãƒ³ã‚¯
Redis as the primary data store? WTF?!
Courtney Couch â€¢ 2013-04-08 Redis is a key-value in memory data store typically used for caches and other such mechanisms to speed up web applications. We however store all our data in Redis as our primary database. The web is abound with warnings and cautionary tales about going this route. There are horror stories about lost data, hitting memory limits, or people unable to effectively manage the
masa_w 2013/04/24
redis

nosql
ãƒªãƒ³ã‚¯
Riak CS Powers Yahoo! Japan's New Cloud Storage
masa_w 2013/02/02
Riak

nosql
ãƒªãƒ³ã‚¯
Rediså¸ƒæ•™æ´»å‹•å ±å‘Š ISUCON ç·¨ - unknownplace.org
æœ€è¿‘ Test::RedisServer ã¨ã‹ã‚‚ã‚ã‚‚ã‚ã¤ãã£ã¦ã¦ã°ã‚Œã¦ã‚‹ã‹ã‚‚ã—ã‚Œã¾ã›ã‚“ãŒã€ã ã„ã¶ Redis æœŸã«ã‚ã‚Šã¾ã—ã¦ã€æœ€è¿‘ã®è¶£å‘³ã¯ï¼Ÿã£ã¦ã„ã†å•ã„ã«ã¯ã ã„ãŸã„Redisã®ã‚½ãƒ¼ã‚¹ã‚’èªã‚€ã“ã¨ã§ã™ã£ã¦ãªãã‚‰ã„ãªã®ã§ã™ãŒã€ memcached ã¨ã‹ã‚·ãƒ³ãƒ—ãƒ«ãª KVS ã¨æ¯”ã¹ã‚‹ã¨ã ã„ã¶æ©Ÿèƒ½ãŒè±Šå¯Œãªã®ã§ä½¿ã„æ–¹ã‚’è¿·ã£ãŸã‚Šã¨ã‹ãã†ã„ã†äº‹ä¾‹ã‚‚ã‚ã‚Šã€å‘¨ã‚Šã«ã‚‚ã†å°‘ã—ä½¿ãˆã‚‹äººã‚’å¢—ã‚„ã•ãªã‘ã‚Œã°åƒ•ã®æ›¸ã„ãŸã‚³ãƒ¼ãƒ‰ãŒå±žäººåŒ–ã—ã¦ã¦ã¤ã‚‰ã„æ„Ÿã˜ã«ãªã‚‹ãªãƒ¼ã£ã¦ã„ã†ã‚ã‘ã§ã€ å¸ƒæ•™æ´»å‹•ã‚’ãŠã“ãªã£ã¦ãŠã‚Šã¾ã—ã¦ã€ãã®ä¸€ç’°ã¨ã—ã¦ ISUCON2 ã«å‚åŠ ã—ã¦ãã¾ã—ãŸã®ã§ãã®å ±å‘Šã§ã™ã€‚ livedoor Techãƒ–ãƒã‚° : #isucon2 ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ãƒ•ã‚©ãƒˆãƒ¬ãƒãƒ¼ãƒˆ æ›´æ–°çµ‚äº† å‰å›žã®å„ªå‹ãƒãƒ¼ãƒ ã«æ··ãœã¦ã‚‚ã‚‰ã£ãŸæ„Ÿã˜ã§ã ã„ã¶ã¤ã„ã¦ã‚‹æ„Ÿã˜ã‚‚ã—ã¾ã™ãŒã€è¦‹äº‹é€£è¦‡ã‚’æžœãŸã›ã€æ‡‡è¦ªä¼šã§ã‚‚ redis redis ã¨é€£å‘¼ã—ã¦ããŸã®ã§ã ã„ã¶èˆˆå‘³æŒã£ãŸæ–¹ã‚‚
masa_w 2012/11/07
redis

nosql
ãƒªãƒ³ã‚¯
http://www.networkworld.com/news/tech/2012/102212-nosql-263595.html
masa_w 2012/10/27
nosql
ãƒªãƒ³ã‚¯
yohei-y:weblog: CAPã®Cã¨ACIDã®C
CAP å®šç†ã¨ BASE ã®æ¦‚å¿µã‚’è€ƒãˆãŸã®ã¯ UCB ã® Brewer å…ˆç”Ÿã§ã€å½¼ã¯ inktomi ã®å‰ã„äººã ã£ãŸã¨ã„ã†ã®ã¯å‰å›žè¿°ã¹ãŸã€‚ å½“æ™‚ã®inktomiã¯Yahoo!ã‚„ Microsoftã€ãã‚Œã«gooã«ã‚‚æ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ã‚’æä¾›ã—ã¦ã„ã¦ã€1å„„ä»¥ä¸Šã®Webãƒšãƒ¼ã‚¸(ãƒ†ãƒ©ãƒã‚¤ãƒˆç´šã®ãƒ‡ãƒ¼ã‚¿)ã‚’æ‰±ã£ã¦ã„ãŸã‚ˆã†ã ã€‚ æ‰‹å…ƒã®WEB+DB PRESS Vol.49 ã®ã¯ã¦ãªãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ãƒªãƒ‹ãƒ¥ãƒ¼ã‚¢ãƒ«è¨˜äº‹ã«ã‚ˆã‚‹ã¨ã€ç¾åœ¨ã®ã¯ã¦ãªãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ã¯1160ä¸‡URLã¨100GBã®HTMLãƒ‡ãƒ¼ã‚¿(åœ§ç¸®æ¸ˆã¿)ã‚’æ‰±ã£ã¦ã„ã‚‹ã‚‰ã—ã„ã®ã§ã€ã–ã£ãã‚Šã„ã£ã¦98å¹´ã®æ™‚ç‚¹ã§inktomi ã¯ç¾åœ¨ã®ã¯ã¦ãƒ–ã®10å€ã®ãƒ‡ãƒ¼ã‚¿ã‚’æ‰±ã£ã¦ã„ãŸã¨ã„ã£ã¦ã‚‚ã„ã„ã€‚inktomiã§ä½¿ã£ã¦ã„ãŸã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿ã®æ€§èƒ½ã¯ç¾åœ¨ã®PCã‚µ ãƒ¼ãƒã«æ¯”ã¹ã‚Œã°1/10ç¨‹åº¦ã®æ€§èƒ½ãªã®ã§ã€ã‚·ã‚¹ãƒ†ãƒ å…¨ä½“ã§ã¿ã‚‹ã¨ç¾åœ¨ã®ã¯ã¦ãƒ–ã®100å€ã®è¦æ¨¡ã«ãªã‚‹ã ã‚ã†ã‹ã€‚ çµæžœçš„ã«ã¯ã€inktom
masa_w 2012/10/10
nosql
ãƒªãƒ³ã‚¯
CAPå®šç†, BASEã®ã¾ã¨ã‚ Â» shmachid dot com
ä»¥å‰ã‹ã‚‰CAPå®šç†ã‚„BASEãŒã‚¤ãƒžã‚¤ãƒè…¹è½ã¡ã—ã¦ã„ãªã‹ã£ãŸã®ã§ã€èª¿ã¹ã¾ã—ãŸã€‚ 1. ACID ã¾ãšã€RDBMSã®ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³å‡¦ç†ã«ãŠã‘ã‚‹ACIDç‰¹æ€§ã¯ä»¥ä¸‹ã§ã‚ã‚‹ã€‚ Atomicity: åŽŸåæ€§ ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³ãŒå®Ÿè¡Œã•ã‚Œã‚‹ã‹ã€å…¨ãã•ã‚Œãªã„ã‹ã®ã©ã¡ã‚‰ã‹ã§ã‚ã‚‹ã€‚ Consistency: ä¸€è²«æ€§ ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã®é–¢ä¿‚åˆ¶ç´„ã‚’ä¿è¨¼ã™ã‚‹ã€‚ Isolation: ç‹¬ç«‹æ€§ ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³ä¸ã«çµŒéŽãŒä»–ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³ã‹ã‚‰å‚ç…§å‡ºæ¥ãªã„ã€‚éš”é›¢æ€§ãŒã‚ã‚‹ã¨ã„ã†ã“ã¨ã€‚ Durability: æ°¸ç¶šæ€§ ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³å®Œäº†å¾Œã€ãƒ‡ãƒ¼ã‚¿ã¯å¤±ã‚ã‚Œãªã„ã€‚è€éšœå®³æ€§ãŒã‚ã‚‹ã¨ã„ã†ã“ã¨ã€‚ 2. CAPå®šç† ç¶šã„ã¦ã€ã‚¯ãƒ©ã‚¦ãƒ‰åŒ–ï¼ˆã‚¯ãƒ©ã‚¦ãƒ‰ã¯åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã¨è€ƒãˆã‚‹ï¼‰ã—ãŸéš›ã¯ACIDç‰¹æ€§ãŒä¿ã¤ã®ã¯éžå¸¸ã«å¤§å¤‰ã§ã‚ã‚‹ã€‚ï¼ˆç„¡ç†ã§ã¯ãªã„ï¼‰ CAPå®šç†ã§ã¯ã€C.A.Pã®ï¼“ã¤ã®å†…ã€åŒæ™‚ã«æº€ãŸã›ã‚‹ã®ã¯2ã¤ã¾ã§ã¨ã„ã†ä¸»å¼µã€‚ Eric Breweræ°ã®CA
masa_w 2012/10/10
nosql
ãƒªãƒ³ã‚¯
Why We Migrated from MongoDB to Riak - DZone
Powering hundreds of thousands of clicks and shares and hundreds of millions of pageviews every month, Shareaholic found itself needing to scale up it's big data architecture. Learn why we chose Riak, what it does for us, and how we imported 100 gigabytes of data from a live Mongo database while maintaining data consistency and zero downtime. I'll discuss the things that went smoothly and the thin
masa_w 2012/10/04
Riak

nosql

MongoDB
ãƒªãƒ³ã‚¯
On moving from CouchDB to Riak
On moving from CouchDB to Riak Written by franck cuny - 07 Mar 2011 This week at work, weâ€™ve started to move our data store from CouchDB to Riak. This represents 35 millions of documents, and a little bit more than 2TB of data. What are we storing We store a lot of data. It all comes from the web, via our various source collectors (feeds aggregator, crawler, APIs clients, ...). To summarize, we st
masa_w 2012/09/21
Riak

nosql
ãƒªãƒ³ã‚¯
NoSQLãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒªãƒ³ã‚°æŠ€æ³•
NoSQLãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒªãƒ³ã‚°æŠ€æ³•.markdown #NoSQLãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒªãƒ³ã‚°æŠ€æ³• åŽŸæ–‡ï¼šNoSQL Data Modeling Techniques Â« Highly Scala ble Blog I translated this article for study. contact matope[dot]ono[gmail] if any probl em. NoSQLãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã¯ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ã€ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã€ä¸€è²«æ€§ã¨ã„ã£ãŸæ§˜ã€…ãªéžæ©Ÿèƒ½è¦ä»¶ã‹ã‚‰æ¯”è¼ƒã•ã‚Œã‚‹ã€‚NoSQLã®ã“ã®å´é¢ã¯å®Ÿè·µã¨ç†è«–ã®ä¸¡é¢ã‹ã‚‰ã‚ˆãç ”ç©¶ã•ã‚Œã¦ã„ã‚‹ã€‚ã‚ã‚‹ç¨®ã®éžæ©Ÿèƒ½ç‰¹æ€§ã¯NoSQLã‚’åˆ©ç”¨ã™ã‚‹ä¸»ãªå‹•æ©Ÿã§ã‚ã‚Šã€NoSQLã‚·ã‚¹ãƒ†ãƒ ã«ã‚ˆãé©ç”¨ã•ã‚Œã‚‹CAPå®šç†ãŒãã†ã§ã‚ã‚‹ã‚ˆã†ã«åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã®åŸºæœ¬çš„åŽŸå‰‡ã ã‹ã‚‰ã ã€‚ä¸€æ–¹ã§ã€NoSQLãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒªãƒ³ã‚°ã¯ã‚ã¾ã‚Šç ”ç©¶ã•ã‚Œã¦ãŠã‚‰ãšã€ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã«è¦‹ã‚‰ã‚Œã‚‹ã‚ˆã†ãªã‚·ã‚¹ãƒ†ãƒžãƒ†ã‚£ãƒƒã‚¯
masa_w 2012/04/17
NoSQL

è¨è¨ˆ
ãƒªãƒ³ã‚¯
NoSQLã«ãŠã‘ã‚‹éžæ£è¦åŒ–çŠ¶æ…‹ã§ã®ãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒ«ã®ä½œã‚Šæ–¹ã‚’ã€ï¼¸ï¼ï¼¬ã‚¹ã‚ãƒ¼ãƒžã®ãƒ‡ã‚¶ã‚¤ãƒ³ãƒ‘ã‚¿ãƒ¼ãƒ³ã‹ã‚‰è€ƒãˆã‚‹ - ã‚¦ã‚£ãƒªã‚¢ãƒ ã®ã„ãŸãšã‚‰ã®ã€ã¾ã¡ã‚ã‚‹ãã€ãŸã¹ã‚ã‚‹ã
ã‚¦ã‚£ãƒªã‚¢ãƒ ã®ã„ãŸãšã‚‰ãŒã€è¡—æ©ãã€é£Ÿã¹ç‰©ã€éŸ³æ¥½ç‰ã®å€‹äººçš„è¦‹è§£ã‚’ä¸»ã«æ›¸ããƒ–ãƒã‚°ã§ã™ï¼ˆãŸã¾ï½žã«ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿ãƒ¼é–¢ä¿‚ã‚‚ï¼‰ ï¼²ï¼¤ï¼¢ã®æ£è¦åŒ–ã™ã‚‹å ´åˆã®ã€ãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒ«ã®ä½œã‚Šæ–¹ã¯ã€æ‰‹æ³•ã¨ã—ã¦ç¢ºç«‹ã—ã¦ã„ã‚‹ã¨ã„ãˆã¾ã™ã€‚ æ£è¦åŒ–ã—ã¦ã€ï¼¥ï¼²ãƒ¢ãƒ‡ãƒ«ã«è½ã¨ã—è¾¼ã‚€ã‚ã‘ã§ã™ã‘ã©ã€ãã‚Œã«ã¤ã„ã¦ã¯ã€ã“ã“ã§æ›¸ãã¾ã—ãŸã€‚ ã˜ã‚ƒã€ï¼²ï¼¤ï¼¢ä»¥å¤–ã®ã‚‚ã®ã«é–¢ã—ã¦ã¯ï¼Ÿ æœ€è¿‘ã€NoSQLã£ã¦ã„ã†ã‚“ã§ã™ã‹ï¼Ÿãã‚Œã«ã¤ã„ã¦ã®ã€ãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒ«ã¯ã©ã†ä½œã‚‹ã‚“ã§ã—ã‚‡ã€‚ã€‚ã€‚ ã‚‚ã¡ã‚ã‚“ã€ï¼®ï½ï¼³ï¼±ï¼¬ï¼ï¼²ï¼¤ï¼¢ä»¥å¤–ã¨ã„ã†ã“ã¨ã¯ã€ã„ã‚ã‚“ãªãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ãŒè€ƒãˆã‚‰ã‚Œã‚‹ã‚ã‘ã§ï¼ˆï¼«ï¼¶ï¼³ã‚‚ãã†ã ã‘ã©ã€ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯åž‹ã ã‚ã†ãŒã€éšŽå±¤åž‹ã ã‚ã†ãŒã€ï¼¸ï¼ï¼¬ï¼¤ï¼¢ã ã‚ã†ãŒã€ã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆæŒ‡å‘ï¼¤ï¼¢ãƒ»ãƒ»ãƒ»ãªã©ãªã©ï¼‰ã€ã„ã‚ã‚“ãªãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ãŒã‚ã‚‹ã‚“ã ã‹ã‚‰ã€ãã‚Œã«ä¼´ã£ã¦ã€ã„ã‚ã‚“ãªãƒ¢ãƒ‡ãƒ«ãŒã‚ã‚‹ã“ã¨ã«ãªã‚Šã¾ã™ã‚ˆãã€‚ ã¨ã„ã†ã“ã¨ã§ã€ã€Œã“ã®ãƒ¢ãƒ‡ãƒ«ã ã‚ï¼ã€ã¨ã„ã†æ±ºå®šçš„ãªãƒ¢ãƒ‡ãƒ«ãŒå‡ºã‚‹ãƒ»ãƒ»ï¼Ÿï¼Ÿã£ã¦ã“ã¨ã¯ãªã„ã¨æ€ã„ã¾ã™ã‘ã©ã€
masa_w 2011/05/13
ãƒ‡ã‚¶ã‚¤ãƒ³ãƒ‘ã‚¿ãƒ¼ãƒ³

nosql
ãƒªãƒ³ã‚¯
https://jp.techcrunch.com/2011/01/18/20110117nosql-graphdb-maker-sones-raises-millions-to-expand-cloud-computing-business/
masa_w 2011/01/18
nosql

GraphDB
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MongoDB Schema Design Goals
Roger Bodamerâ€™s slidedeck on designing schemas for Mongo DB. A nice addition to our Mongo DB schema design: Things to keep in mind as goals when designing for Mongo DB: avoid anomalies when inserting, updating, or deletingminimize redesign when extending the schemamake the model informative to usersavoid bias towards a particular style of queryOriginal title and link: Mongo DB Schema Design Goals (NoS
masa_w 2010/12/01
MongoDB

nosql
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Introduction to Sharding with MongoDB
Sharding allows databases to automatically redistribute and rebalance data across servers. This enables scaling collections beyond a single server's storage limitations and improves performance. When sharding, it is important to choose an appropriate sharding key to optimize query performance and allow automatic redistribution of data as needs change over time. Proper use of indexes is also critic
masa_w 2010/11/26
MongoDB

nosql
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Sharding with MongoDB (Eliot Horowitz)
This document summarizes Mongo DB sharding. It discusses how sharding allows databases to scale wider rather than higher to overcome limits of vertical scaling. Sharding partitions data into chunks that are distributed across shards in a consistent and automatic way, with minimal functionality loss compared to a single master. It describes how writes, queries, operations, and balancing work in a sh
masa_w 2010/11/25
MongoDB

nosql
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Foursquareã®MongoDBãŒæ©Ÿèƒ½åœæ¢
Spring Bootã«ã‚ˆã‚‹APIãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰æ§‹ç¯‰å®Ÿè·µã‚¬ã‚¤ãƒ‰ ç¬¬2ç‰ˆ ä½•åƒäººã‚‚ã®é–‹ç™ºè€…ãŒã€InfoQã®ãƒŸãƒ‹ãƒ–ãƒƒã‚¯ã€ŒPractical Guide to Building an API Back End with Spring Bootã€ã‹ã‚‰ã€Spring Bootã‚’ä½¿ã£ãŸREST APIæ§‹ç¯‰ã®åŸºç¤Žã‚’å¦ã‚“ã ã€‚ã“ã®æœ¬ã§ã¯ã€å‡ºç‰ˆæ™‚ã«æ–°ã—ããƒªãƒªãƒ¼ã‚¹ã•ã‚ŒãŸãƒãƒ¼ã‚¸ãƒ§ãƒ³ã§ã‚ã‚‹ Spring Boot 2 ã‚’ä½¿ç”¨ã—ã¦ã„ã‚‹ã€‚ã—ã‹ã—ã€Spring Boot3ãŒæœ€è¿‘ãƒªãƒªãƒ¼ã‚¹ã•ã‚Œã€é‡è¦ãªå¤‰...
masa_w 2010/11/25
nosql

MongoDB
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MongoDB - On Distributed Consistency -- Part 1
On Distributed Consistency â€” Part 1 See also: Part 2 - Eventual Consistency Part 3 - Network Partitions Part 4 - Multi Data Center Part 5 - Multi Writer Eventual Consistency Part 6 - Consistency Chart For distributed databases, consistency models are a topic of huge importance. Weâ€™d like to delve a bit deeper on this topic with a series of articles, discussing subjects such as what model is right
masa_w 2010/11/25
nosql

MongoDB
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