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pcod id:pcod

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

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yrmcds 0.9.0 ãƒªãƒªãƒ¼ã‚¹ - Cybozu Inside Out | ã‚µã‚¤ãƒœã‚¦ã‚ºã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã®ãƒ–ãƒã‚°
@ymmt2005 ã“ã¨å±±æœ¬æ³°å®‡ã§ã™ã€‚ ä»Šå›žã¯ memcached äº’æ›ã§å†—é•·æ§‹æˆã‚’ç°¡å˜ã«çµ„ã‚ã‚‹è‡ªç¤¾è£½ KVS ã§ã‚ã‚‹ yrmcds ã®ãƒªãƒªãƒ¼ã‚¹ã‚’ã”æ¡ˆå†…ã—ã¾ã™ã€‚ ... ã“ã® Redis å…¨ç››ãªã”æ™‚ä¸–ã«ãªã‚“ã§ï¼Ÿã¨ã‹ã€repcached ã‚„ Kyoto Tycoon ãŒã‚ã‚‹ã˜ã‚ƒãªã„ã€ã¨ã„ã£ãŸãƒ„ãƒƒã‚³ãƒŸã®åµãŒèžãˆã¦ããã†ã§ã™ã€‚ã‚ã‹ã£ã¦ã¾ã™ã€ã‚ã‹ã£ã¦ã¾ã™ã‹ã‚‰ç‰©ã‚’æŠ•ã’ãªã„ã§ï¼ é †ã‚’è¿½ã£ã¦èª¬æ˜Žã—ã¾ã™ã®ã§ã€æ‰¹åˆ¤ã¯ãã‚Œã‹ã‚‰ã«ã—ã¦ãã ã•ã„ï¼ ä½•ãŒæ¬²ã—ã„ã®ã‹ ç§ã¯æ—¥é ƒ cybozu.com ã®ã‚¤ãƒ³ãƒ•ãƒ©ã§å‹•ä½œã™ã‚‹ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ã‚’é–‹ç™ºã—ã¦ã„ã¾ã™ã€‚ãƒªãƒªãƒ¼ã‚¹å¾Œã‚‚ã†ã™ãï¼’å¹´ã«ãªã‚Šã¾ã™ãŒã€ãŠè”æ§˜ã§ 4,000 ç¤¾ä»¥ä¸Šã«ã”åˆ©ç”¨ã„ãŸã ãã¾ã§ã«ãªã‚Šã¾ã—ãŸã€‚å•†å£²ç¹ç››ã§å¬‰ã—ã„ã®ã§ã™ãŒã€é‹ç”¨å´ã¯æ—¥ã€…å¢—ãˆã‚‹ãƒ‡ãƒ¼ã‚¿ã¨ã‚¢ã‚¯ã‚»ã‚¹ã‚’æŒãã¹ãå¥®é—˜ã—ã¦ã„ã¾ã™ã€‚ ã“ã“ã®ã¨ã“ã‚å•é¡Œã«ãªã£ã¦ã„ãŸã®ãŒã€MySQL ã«ä¿å˜ã—ã¦ã„ã‚‹ã‚»ãƒƒã‚·ãƒ§ãƒ³æƒ…å ±ã§ã—ãŸã€‚ã‚¢ãƒ—ãƒª
pcod 2013/07/09
kvs
ãƒªãƒ³ã‚¯
åˆ†æ•£ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã€ŒHBaseã€ã®å®‰å®šé‹ç”¨ã‚’ç›®æŒ‡ã—ã¦ - Preferred Networks Research & Development
1å¹´çµŒã£ã¦iPhone4ã®é›»æ± ãŒãƒ˜ã‚¿ã£ã¦ããŸã€å¤ªç”°ã§ã™ã€‚ æŒ‡æ•°é–¢æ•°çš„ã«ã‚¨ãƒ³ãƒˆãƒªæ•°ãŒå°‘ãªããªã£ã¦ããŸæœ¬ãƒ–ãƒã‚°ã§ã™ãŒwã€æ™¯æ°—ä»˜ã‘ã®ãŸã‚ã«ã‚¨ãƒ³ãƒˆãƒªã‚’æŠ•ç¨¿ã—ãŸã„ã¨æ€ã„ã¾ã™ï¼æœ¬æ—¥ã¯HBaseã«ã¤ã„ã¦ã§ã™ã€‚ Linux ã¨ Hadoop ã¨ HBase ã¨ ZooKeeper ã«è©³ã—ã„ã‚ãªãŸï¼ã‚ãªãŸãŒã‚¿ãƒ¼ã‚²ãƒƒãƒˆã§ã™ã€‚ HBaseã¨ã¯? HBaseã¨ã¯ã€HDFS (Hadoop Distributed File System)ä¸Šã«æ§‹ç¯‰ã•ã‚ŒãŸåˆ†æ•£ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã§ã™ã€‚å¤§é‡ã®éžå¸¸ã«ç´°ã‹ã„ãƒ‡ãƒ¼ã‚¿ã‚’ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ã«èªã¿æ›¸ãå‡ºæ¥ã‚‹ã®ãŒç‰¹å¾´ã§ã™ã€‚æœ€è¿‘ã§ã¯Facebook Messageã®åŸºç›¤æŠ€è¡“ã¨ã—ã¦ä½¿ç”¨ã•ã‚ŒãŸäº‹ã§æ³¨ç›®ã‚’é›†ã‚ã¦ã„ã¾ã™ã€‚ HBaseå…¬å¼ã‚µã‚¤ãƒˆ Apache HBase ãƒ–ãƒƒã‚¯ ä¿å˜ã•ã‚ŒãŸãƒ‡ãƒ¼ã‚¿ã¯HDFSä¸Šã«ä¿å˜ã•ã‚Œã€HDFSã®ä»•çµ„ã¿ã«ã‚ˆã£ã¦ãƒ¬ãƒ—ãƒªã‚±ãƒ¼ã‚·ãƒ§ãƒ³ã•ã‚Œã‚‹ãŸã‚å®‰å…¨ã«ãƒ‡ãƒ¼ã‚¿ã‚’ä¿æŒã™ã‚‹ã“ã¨ãŒå‡ºæ¥ã¾ã™ã€‚ ã¾
pcod 2011/05/09
hbase

pfi

kvs
ãƒªãƒ³ã‚¯
GitHub - google/leveldb: LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
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pcod 2011/04/17
kvs

snappy
ãƒªãƒ³ã‚¯
Outerthought :: Lily - the Scalable Content Repository
What is Lily? Lily does Smart Data, at Scale.Â Lily is the first Big Data content storage and search repository,Â built on top ofÂ Apache HBase and SOLR. It is made available under the Apache license by Outerthought. Lily is a scala ble foundation for large-scale content applications, such as SaaS-style content management, archiving, media publishing, and document management. It offers a flexible data
pcod 2011/02/15
kvs

hbase

Solr
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Redis - The Real-time Data Platform
# Create a vector index using the HNSW algorithm, 768 dimension length, and inner product distance metric > FT.CREATE idx-videos ON HASH PREFIX 1 video: SCHEMA content_vector VECTOR HNSW 6 TYPE FLOAT32 DIM 768 DISTANCE_METRIC IP content TEXT metadata TEXT # Add a video vector with metadata > HSET video:0 content_vector â€œ\xa4q\t=\xc1\xdes\xbdZ$<\xbd\xd5\xc1\x99<b\xf0\xf2<x[â€¦\xf8<â€ content â€œSUMMARY:
pcod 2011/02/12
redis

kvs
ãƒªãƒ³ã‚¯
fallabs.com
fallabs.com 2023 è‘—ä½œæ¨©. ä¸è¨±è¤‡è£½ ãƒ—ãƒ©ã‚¤ãƒã‚·ãƒ¼ãƒãƒªã‚·ãƒ¼
pcod 2010/11/28
kyotocabinet

kyototycoon

kvs

db
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é–‹ç™ºãƒ¡ãƒ¢: memcachedã¨Kyoto Tycoonã®ç©ºé–“åŠ¹çŽ‡
Kyoto CabinetãŠã‚ˆã³Kyoto Tycoonã«æ–°ãŸã«å°Žå…¥ã•ã‚ŒãŸã€ŒStashDBã€ã‚’ä½¿ã†ã¨memcachedã‚ˆã‚Šã‚‚ç©ºé–“åŠ¹çŽ‡ã‚’å‘ä¸Šã•ã›ã‚‰ã‚Œã‚‹ã¨ã„ã†è©±ã€‚ StashDBã¨ã¯ å‰å›žã®è¨˜äº‹ã§èª¬æ˜Žã—ãŸã‚ˆã†ã«ã€Kyoto Cabinetã§ã¯ãƒãƒ¼ã‚«ãƒ«MapReduceã®ã‚ãƒ£ãƒƒã‚·ãƒ¥ã¨ã—ã¦TinyHashMapã¨ã„ã†ã‚¯ãƒ©ã‚¹ã‚’å®Ÿè£…ã—ã¦çœãƒ¡ãƒ¢ãƒªåŒ–ã‚’å›³ã£ã¦ã„ã‚‹ã€‚ä¸å¯§ã«ã‚·ãƒªã‚¢ãƒ©ã‚¤ã‚ºã—ã¦ãƒ‡ãƒ¼ã‚¿ã‚’è©°ã‚ã¦ã„ãã¨ã‹ãªã‚Šãƒ¡ãƒ¢ãƒªã‚’ç¯€ç´„ã§ãã‚‹ã‚‚ã®ãªã®ã ã€‚ åŒã˜æ§‹é€ ã‚’DBMã®ã‚¤ãƒ³ã‚¿ãƒ¼ãƒ•ã‚§ã‚¤ã‚¹ã«ã—ãŸã®ãŒStashDBã§ã‚ã‚‹ã€‚ProtoHashDB, ProtoTreeDB, CacheDB, GrassDB, HashDB, TreeDB, DirDB, ForestDBã«ç¶šãç¬¬9ç•ªç›®ã®DBMã¨ã„ã†ã“ã¨ã«ãªã‚‹ã€‚ã‚‚ã¡ã‚ã‚“ã€ãƒžãƒ«ãƒã‚¹ãƒ¬ãƒƒãƒ‰ã‚»ãƒ¼ãƒ•ã«ã—ã¦ã€ãƒ¬ã‚³ãƒ¼ãƒ‰å˜ä½ã®ç²’åº¦ã§ãƒãƒƒã‚¯ã‚’æ–½ã—ã¦ä¸€è²«æ€§ã‚’ç¢ºä¿ã—ã€Visitorã‚„Curso
pcod 2010/11/28
kvs

performance

kyotocabinet
ãƒªãƒ³ã‚¯
SNA Projects Blog : Tech Talk: Michael Deerkoski (Flickr) â€” â€œContinuous Deployment at Flickrâ€
Hire the best. At 10x the speed.Hire the best. At 10x the speed.Screen and interview candidates 10x faster with MOPID AI Recruiter that saves upto 80% of your time and resources. Hiring 100+ positions? Tryâš¡Bl itzhiringâš¡for a change!Hiring 100+ positions?Try âš¡Bl itzhiringâš¡ for a changeWe get it. Large scale hiring costs a lot. What if you could hire the perfect talent AND save up to 80% resources? We
pcod 2010/10/11
kvs

linkedin
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Membase.org
Whether youâ€™re new to Couchbase or a longtime user, our Community Team and thousands of developers are here to accompany you on your Couchbase journey! Join the Couchbase community Explore all the ways you can connect, learn, and share with other developers. Letâ€™s talk Couchbase Exchange ideas in real time, connect with fellow Couchbasers, and most importantly share cat photos!
pcod 2010/06/25
kvs

memcached
ãƒªãƒ³ã‚¯
Kyoto Cabinet 1.0.0ãƒªãƒªãƒ¼ã‚¹ï¼ - mixi engineer blog
å¤ãŒè¿‘ã¥ãã¨ã‚¦ã‚ã‚¦ã‚ã—ã¦ãã‚‹mikioã§ã™ã€‚æ˜¨æ—¥ã¤ã„ã«ãƒªãƒªãƒ¼ã‚¹ã•ã‚ŒãŸKyoto Cabinet 1.0ã«ã¤ã„ã¦ä»Šå›žã¯å ±å‘Šã—ã¾ã™ã€‚ 1.0ã®ä½ç½®ã¥ã‘ ã‚³ãƒŸãƒ¥ãƒ‹ãƒ†ã‚£æ¯Žã‚„è£½å“æ¯Žã«ãƒãƒ¼ã‚¸ãƒ§ãƒ³ç•ªå·å‰²ã‚Šå½“ã¦ã®æ–¹é‡ã¯ç•°ãªã‚‹ã‚ã‘ã§ã™ãŒã€ç§ã®å€‹äººçš„ãªãƒãƒªã‚·ãƒ¼ã§ã¯ã€1.0ã«ã¯ç‰¹åˆ¥ãªæ„å‘³ãŒã‚ã‚Šã¾ã™ã€‚ã™ãªã‚ã¡ã€0.xã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã¯betaç‰ˆçš„ãªä½ç½®ã¥ã‘ã§ã€ã€Œå®Ÿã‚µãƒ¼ãƒ“ã‚¹ã«ä½¿ã†ã®ã¯ã¡ã‚‡ã£ã¨å¾…ã£ãŸæ–¹ãŒã„ã„ã§ã™ã‚ˆã€ã¨ã„ã†ã“ã¨ã‚’æ„å‘³ã—ã¾ã™ã€‚ä¸€æ–¹ã§ã€1.xã¯stableç‰ˆçš„ãªä½ç½®ã¥ã‘ã§ã€ã€Œã‚ˆã‚ã—ã‘ã‚Œã°å®Ÿã‚µãƒ¼ãƒ“ã‚¹ã§ã‚‚ä½¿ã£ã¦ã¿ã¦ãã ã•ã„ã€ã¨ã„ã†ã“ã¨ã‚’æ„å‘³ã—ã¾ã™ã€‚ç§ãŒstableç‰ˆã«è¨å®šã™ã‚‹åŽŸå‰‡ã‚’ä»¥ä¸‹ã«åˆ—æŒ™ã—ã¾ã™ã€‚ å®‰å®šç¨¼åƒã‚’è‡³ä¸Šå‘½é¡Œã¨ã™ã‚‹ï¼ˆãƒã‚°ãŒã‚ã‚Œã°ãã®ä¿®æ£ã‚’æœ€å„ªå…ˆã™ã‚‹ï¼‰ APIã‚’å¤‰æ›´ã—ãªã„ï¼ˆå¤‰æ›´ã™ã‚‹ã¨ã—ã¦ã‚‚å¾Œæ–¹äº’æ›æ€§ã‚’ç¶æŒã™ã‚‹ï¼‰ DBãƒ•ã‚¡ã‚¤ãƒ«ã®ãƒ•ã‚©ãƒ¼ãƒžãƒƒãƒˆã‚’å¤‰æ›´ã—ãªã„ï¼ˆå¤‰æ›´ã™ã‚‹ã¨ã—ã¦ã‚‚å¾Œæ–¹äº’æ›æ€§ã‚’ç¶æŒã™ã‚‹ï¼‰ ãªã‚‹ã¹ãæ©Ÿèƒ½è¿½åŠ
pcod 2010/05/25
mixi

kvs

kyotocabinet
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kumofsã¯ãªãœã‚¹ã‚±ãƒ¼ãƒ«ã™ã‚‹ã‹ - Blog by Sadayuki Furuhashi
å…ˆæ—¥ã€åˆ†æ•£Key-valueã‚¹ãƒˆã‚¢ kumofs ã‚’å…¬é–‹ã—ã¾ã—ãŸã€‚ å¤šãæ–¹ã‹ã‚‰åéŸ¿ã¨ãƒ•ã‚£ãƒ¼ãƒ‰ãƒãƒƒã‚¯ã‚’ã„ãŸã ã„ã¦ã„ã¾ã™ã€‚ã‚ã‚ŠãŒã¨ã†ã”ã–ã„ã¾ã™ã€‚ ä»Šå›žã¯ã€kumofs ã¯ãªãœã‚¹ã‚±ãƒ¼ãƒ«ã™ã‚‹ã®ã‹ã€ãªãœã‚¹ã‚±ãƒ¼ãƒ«ã™ã‚‹ã¨è¨€ãˆã‚‹ã®ã‹ãƒ¼ã¨ã„ã†ã“ã¨ã«ã¤ã„ã¦ç´¹ä»‹ã—ãŸã„ã¨æ€ã„ã¾ã™ã€‚ ã¨ã“ã‚ã§ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ã¨ã¯ä½•ã‹ï¼Ÿ ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ã¨ã¯ã€åˆ©ç”¨è€…ã‚„ä»•äº‹ã®å¢—å¤§ã«é©å¿œã§ãã‚‹èƒ½åŠ›ãƒ»åº¦åˆã„ ã¨ã•ã‚Œã¦ã„ã¾ã™ï¼ˆç«¯çš„ï¼ï¼‰*1 ã€‚Scalability ã‚’æ—¥æœ¬èªžã«ã™ã‚‹ã¨ã€æ‹¡å¼µæ€§ ã¨è¨³ã•ã‚Œã‚‹ã‚ˆã†ã§ã™ã€‚ ãŸã ä¸€å£ã§ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ã¨è¨€ã£ã¦ã‚‚ã€æ§˜ã€…ãªå´é¢ãŒã‚ã‚Šã¾ã™ã€‚ITã‚·ã‚¹ãƒ†ãƒ ã§ã¯ä¸»ã«ã¯å‡¦ç†æ€§èƒ½ã¨é‹ç”¨ã«é–¢ã™ã‚‹ã“ã¨ã‚’æŒ‡ã™å ´åˆãŒå¤šã„ã¨æ€ã„ã¾ã™ãŒ*2ã€ãã®ä¸ã«ã‚‚æ§˜ã€…ãªå´é¢ãŒã‚ã‚Šã¾ã™ã€‚ ãªãœã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ãŒå¿…è¦ã‹ ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ã¯ ã‚·ã‚¹ãƒ†ãƒ ãªã©ãŒæŒã¤ã¹ãæœ›ã¾ã—ã„ç‰¹æ€§ ã§ã‚ã£ã¦ã€é«˜ã„ã«è¶Šã—ãŸã“ã¨ã¯ã‚ã‚Šã¾ã›ã‚“ã€‚ã—ã‹ã—ã€é«˜ã„ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“ãƒªãƒ†ã‚£ã¯ã‚¿
pcod 2010/02/06
kvs

scalability
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åˆ†æ•£Key-Valueã‚¹ãƒˆã‚¢ã€Œkumofsã€ã‚’å…¬é–‹ã—ã¾ã—ãŸï¼ - Blog by Sadayuki Furuhashi
åˆ†æ•£Key-Valueã‚¹ãƒˆã‚¢ kumofs ã‚’ã€æœ¬æ—¥ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ã¨ã—ã¦ãƒªãƒªãƒ¼ã‚¹ã—ã¾ã—ãŸï¼ kumofs@SourceForge kumofsé–¢é€£è³‡æ–™ã¾ã¨ã‚ kumofsã¨ã¯ï¼Ÿ kumofsï¼ˆã‚¯ãƒ¢ã‚¨ãƒ•ã‚¨ã‚¹ï¼‰ã¯ã€å®Ÿç”¨æ€§ã‚’é‡è¦–ã—ãŸåˆ†æ•£ãƒ‡ãƒ¼ã‚¿ã‚¹ãƒˆã‚¢ã§ã™ã€‚ãƒ¬ãƒ—ãƒªã‚±ãƒ¼ã‚·ãƒ§ãƒ³æ©Ÿèƒ½ã‚’å‚™ãˆã€ä¸€éƒ¨ã®ã‚µãƒ¼ãƒãƒ¼ã«éšœå®³ãŒç™ºç”Ÿã—ã¦ã‚‚å‹•ä½œã—ç¶šã‘ã¾ã™ã€‚å˜ä½“ã§ã‚‚é«˜ã„æ€§èƒ½ã‚’æŒã¡ãªãŒã‚‰ã€ã‚µãƒ¼ãƒãƒ¼ã‚’è¿½åŠ ã™ã‚‹ã“ã¨ã§èªã¿ãƒ»æ›¸ãä¸¡æ–¹ã®æ€§èƒ½ãŒå‘ä¸Šã™ã‚‹ç‰¹å¾´ã‚’æŒã¡ã€ä½Žã‚³ã‚¹ãƒˆã§æ¥µã‚ã¦é«˜é€Ÿãªã‚¹ãƒˆãƒ¬ãƒ¼ã‚¸ã‚·ã‚¹ãƒ†ãƒ ã‚’æ§‹ç¯‰ãƒ»é‹ç”¨ã§ãã¾ã™ã€‚ kumofsã®å¤§ããªç‰¹å¾´ã¯ã€ã‚·ã‚¹ãƒ†ãƒ ã®æ§‹æˆã®ç°¡å˜ã«å¤‰æ›´ã§ãã‚‹ç‚¹ã§ã™ã€‚ã‚·ã‚¹ãƒ†ãƒ ã‚’æ¢ã‚ã‚‹ã“ã¨ãªãã€ç°¡å˜ãªæ‰‹é †ã§ã‚µãƒ¼ãƒãƒ¼ã‚’è¿½åŠ ã—ãŸã‚Šå¾©æ—§ã—ãŸã‚Šã§ãã¾ã™ã€‚ã‚¢ãƒ—ãƒªã‚±ãƒ¼ã‚·ãƒ§ãƒ³ã«ã¯ä¸€åˆ‡å½±éŸ¿ã‚’ä¸Žãˆã¾ã›ã‚“ã€‚ ã¾ãŸkumofsã¯ã€åºƒãåˆ©ç”¨ã•ã‚Œã¦ã„ã‚‹åˆ†æ•£ã‚ãƒ£ãƒƒã‚·ãƒ¥ã‚·ã‚¹ãƒ†ãƒ ã®ã€Œmemcachedã€ã¨äº’æ›æ€§ã®ã‚ã‚‹ãƒ—ãƒãƒˆã‚³ãƒ«ã‚’å®Ÿè£…
pcod 2010/02/06
kvs
ãƒªãƒ³ã‚¯
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, Hyperta ble AmazonDynamo, Voldemort, Cassendra, Riak Redis CouchDB, Mongo DB These solutions has a number of characteristics in common K
pcod 2009/11/25
nosql

kvs

ã¾ã¨ã‚
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ãªã‚“ã‹ Go ã§æ›¸ãã®ãŒæµè¡Œã£ã¦ã‚‹ã¿ãŸã„ãªã®ã§ - moriyoshiã®æ—¥è¨˜
è¿½è¨˜:ã€Œkzk's blogã€ã®ã€ŒWriting TokyoCabinet wrapper for Go languageã€ã§ç´¹ä»‹å¾¡ç¤¼ã€‚ã“ã®è¨˜äº‹ã¯ cgo ã‚’ä½¿ã£ãŸ TokyoCabinet ã®ãƒ©ãƒƒãƒ‘ãƒ¼ã®æ›¸ãæ–¹ã‚’è§£èª¬ã—ã¦ã„ã‚‹ã®ã§ã€ä¸‹è¨˜ã®ã‚³ãƒ¼ãƒ‰ã¨çµ„ã¿åˆã‚ã›ã¦æœ¬å½“ã« tc ãŒ backend ã«ãªã£ã¦ã„ã‚‹ KVS ã‚’æ›¸ã„ã¦ã¿ã‚‹ã®ã‚‚ã‚ˆã„ã‹ã‚‚ã€‚ ã€Žæ—©é€Ÿ Go è¨€èªžã‚’è©¦ã—ã¦ã¿ã‚‹ï¼ã€ã¨ã‹ã€‚ ã€ŽGo ã§ç„¡é§„ã«ãƒãƒ£ãƒ³ãƒãƒ«ã‚’ä½¿ã£ã¦ã‚¯ã‚¤ãƒƒã‚¯ã‚½ãƒ¼ãƒˆã®ã‚ˆã†ãªã‚‚ã®ã‚’æ›¸ã„ã¦ã¿ãŸã€ã¨ã‹ã€‚ ã“ã¡ã‚‰ã¯ã¨ã„ã†ã¨ã€è©¦ã—ã« memcache ãƒã‚¤ãƒŠãƒªãƒ—ãƒãƒˆã‚³ãƒ«ã§é€šä¿¡ã™ã‚‹ KVS ã‚‚ã©ãã‚’æ›¸ã„ãŸã€‚ ã‚µãƒ¼ãƒã®ã‚¤ãƒ™ãƒ³ãƒˆãƒ«ãƒ¼ãƒ—ã§ go ã™ã‚Œã°å…¨éƒ¨æ¸ˆã‚€ã®ãŒæ¥½ã¡ã‚“ã§ã™ãã€‚ è¿½è¨˜: HandleConn() ã®ä¸ã§ã€backend_ch ã‚’ backend ã¨ã®é€ä¿¡ã¨å—ä¿¡ä¸¡æ–¹ã«ä½¿ã£ã¦ã„ãŸã®ã ã‘ã©ã€ã“ã“ã«ã‚ã‚‹ã‚ˆã†ã«ã€ã¾ã£ãŸãèª¤ã‚Šã ã¨ã„ã†ã“ã¨ãŒåˆ†
pcod 2009/11/16
kvs

go
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Google Code Archive - Long-term storage for Google Code Project Hosting.
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pcod 2009/10/25
kvs

ruby
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Kazuho@Cybozu Labs: Mycached: memcached protocol support for MySQL
It is a well-known fact that the bottlenecks of MySQL does not exist in its storage engines, but rather in the core, for example, its parser and execution planner.Â Last weekend I started to wonder how fast MySQL could be if those bottlenecks were skipped.Â Not being able to stop my curiousity, I startedÂ adding memcached proctol support to MySQL as a UDF.Â And that is Mycached. From what I unders
pcod 2009/08/28
memcached

mysql

kvs
ãƒªãƒ³ã‚¯
CDB++: C++ implementation of Constant Database
C++ implementation of Constant Database (CDB++) Introduction Constant Database PlusPlus (CDB++) is a C++ implementation of hash database specialized for serialization and retrieval of static associations between keys and their values. The database provides several features: Fast look-ups. This library implements the data structure of the Constant Database proposed by Daniel J. Bernstein.Low footpr
pcod 2009/07/15
kvs
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techZING! 8 â€“ Dude, Whereâ€™s My Database?!
Podcast: Play in new window | Download Subscribe: iTunes | Android | RSS Justin & Jason talk to Jonathan Ellis about how Facebookâ€™s open sourced Cassandra Project took lessons learned from Amazonâ€™s Dynamo and Googleâ€™s BigTable to tackle the difficult probl em of building a highly scala ble, always available, distributed data store. We also discuss how to join, get taken seriously and get commit acce
pcod 2009/07/12
kvs

cassandra

voldemort

erlang

nosql
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braindump: NOSQL debrief
Saturday, 13 June 2009 NOSQL debrief The relatively young but rapidly growing "nosql" community met last Thursday in San Francisco. The idea was to give attendees a solid introduction to how distributed, non relational databases work as well as an overview of the various projects out there. If I may say so myself we succeeded in doing both. Thanks to all the presenters for very interesting talks a
pcod 2009/07/11
kvs

nosql

voldemort
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Google Code Archive - Long-term storage for Google Code Project Hosting.
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pcod 2009/07/05
Osmos provides on-disk ordered key-value tables for Erlang

erlang

kvs
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