Cloudian nosql casestudy_20120318
2012å¹´3月18日開催InfoTalkã«ãŠã‘るプレゼンテーション資料ã§ã™ã€‚Cloudianã®æ¦‚è¦ã€Cloudianã¸ã®Cassandraã¨Redisã®å®Ÿè£…ã€NOSQLデータベースã®æ€§èƒ½æ¯”較ã€ç‹¬è‡ªé–‹ç™ºã®HyperStoreã«ã¤ã„ã¦èª¬æ˜Žã—ã¦ã„ã¾ã™ã€‚Read less
第1回分散処ç†ãƒ¯ãƒ¼ã‚¯ã‚·ãƒ§ãƒƒãƒ—ã®æ„Ÿæƒ³ - ã²ã—ã ã¾ã®å¤‰æ›´å±¥æ´
ã²ã—ã ã¾ï¼¨ï¼°ã®æ›´æ–°å±¥æ´ã€‚ 主ã«ï¼´ï¼²ï¼°ï¼§ãƒªãƒ—レイã®å…ƒãƒã‚¿é›†ã€ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°æŠ€è¡“メモã¨è‡ªä½œã‚½ãƒ•ãƒˆã€å¥½ããªã‚²ãƒ¼ãƒ や音楽ã§ã™ã€‚ 「第1回分散処ç†ãƒ¯ãƒ¼ã‚¯ã‚·ãƒ§ãƒƒãƒ— in Tokyoã€ã«å‚åŠ ã§ãã¾ã—ãŸã®ã§ã€ãã®æ„Ÿæƒ³ãªã©ã€‚ （長らãè£œæ¬ 3番目ã ã£ãŸã®ã§ä»Šå›žã¯ç„¡ç†ã‹ãªãƒ¼ã¨æ€ã£ã¦ãŸã‚“ã ã‘ã©ã€ãŽã‚ŠãŽã‚Šã§ã‚ャンセルãŒå‡ºãŸã®ã§å…¥ã‚ŒãŸï¼‰ Togetter： 「第1回分散処ç†ãƒ¯ãƒ¼ã‚¯ã‚·ãƒ§ãƒƒãƒ— in Tokyo〠#dist_study 資料ã®å ´æ‰€ã¯okuyamaooã•ã‚“ã®ã€Œç¬¬1回分散処ç†ãƒ¯ãƒ¼ã‚¯ã‚·ãƒ§ãƒƒãƒ— in Tokyoã€ã‚’開催ã—ã¾ã—ãŸã«å…¨éƒ¨å‡ºã¦ã„ã¾ã™ã€‚ å„DBMS（分散KVS）ã®ç´¹ä»‹ã‚’1ã¤å½“ãŸã‚Š15分。ã®äºˆå®šãŒã€Q&AãŒå…¥ã£ãŸã‚Šã—ã¦ç››ã‚Šä¸ŠãŒã‚Šã€ã‘ã£ã“ã†ä¼¸ã³ä¼¸ã³ã«(笑) 全般的ãªæ„Ÿæƒ³ã¨ã—ã¦ã¯ã€ã‚„ã¯ã‚ŠDBMS（分散KVS）を実際ã«ä½œã£ã¦ã„る人ã¯ã™ã”ã„(笑) æ–¹å¼ã‚’考ãˆã¦å®Ÿè£…ã—ã¦ã¿ã¦è©¦è¡ŒéŒ¯èª¤ã—ã¦ã„ã‚‹ã ã‚ã†ã‹ã‚‰ã€ä»–ã®DBMSã«ã¤
NoSQL GraphDB
I received some constructive criticism regarding my previous blog in NoSQL patterns that I covered only the key/value store but have left out Graph DB. The Property Graph Model A property graph is a collection of Nodes and Directed Arcs. Each node represents an entity and has an unique id as well as a Node Type. The Node Type defines a set of metadata that the node has. Each arc represents a unidi
What we talk about when we talk about NewSQL — Too much information
Yesterday The 451 Group published a report asking “How will the database incumbents respond to NoSQL and NewSQL?†That prompted the pertinent question, “What do you mean by ‘NewSQL’?†Since we are about to publish a report describing our view of the emerging database landscape, including NoSQL, NewSQL and beyond (now available), it probably is a good time to define what we mean by NewSQL (I haven’
Riak Wiki: Welcome to the Riak Wiki
Riak is a Dynamo-inspired database that is being used in production by companies like Mozilla and Comcast. Riak scales predictably and easily and simplifies development by giving users the ability to quickly prototype, test, and deploy their applications. A truly fault-tolerant system, Riak has no single point of failure. No machines are special or central in Riak, so developers and operations pro
Apache HBase 入門 (第１回)
The document discusses big data and Hadoop concepts. It covers Hadoop operations like put, get, scan, filter, delete as well as join and group by. It also discusses the different types of data access patterns like random write, sequential read, sequential write and random read. The document focuses on big data, Hadoop operations, and data access patterns.Read less
Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison :: Software architect Kristof Kovacs
Hello, I’m Kristof, a human being like you, and an easy to work with, friendly guy. I've been a programmer, a consultant, CIO in startups, head of software development in government, and built two software companies. Some days I’m coding Golang in the guts of a system and other days I'm wearing a suit to help clients with their DevOps practices. While SQL databases are insanely useful tools, their
Distributed Programming and Data Consistency w/ Notes
This document discusses distributed programming and data consistency. It defines consistency as how systems and observers perceive the state of a system over time. Consistency has a time aspect, where expected and unexpected sequences of states can occur. Distributed systems like caching introduce inconsistencies when data is replicated across servers. The CAP theorem states that a distributed sys
GitHub - ahiguti/HandlerSocket-Plugin-for-MySQL: NOTE: THIS REPO IS JUST A COPY. The upstream repo of HandlerSocket has been moved to https://github.com/DeNA/HandlerSocket-Plugin-for-MySQL .
----------------------------------------------------------------------------- HandlerSocket plugin for MySQL Copyright (c) 2010 DeNA Co.,Ltd. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditio
TM Emerging Trends in Data Storage and Processing Kevin Weil -- @kevinweil Analytics Lead, Twitter Stanford CS 145 November 29, 2010 Monday, November 29, 2010 Giving a talk about SQL and NoSQL in CS145 at Stanford. Lots of ##s! 1 minute ago via Twitter f
TM Emerging Trends in Data Storage and Processing Kevin Weil -- @kevinweil Analytics Lead, Twitter Stanford CS 145 November 29, 2010 Monday, November 29, 2010 Giving a talk about SQL and NoSQL in CS145 at Stanford. Lots of ##s! 1 minute ago via Twitter for iPhone Retweeted by 1 person kevinweil Monday, November 29, 2010 Introduction ‣ A Review of SQL ‣ Pop Quiz ‣ Storing Tweets ‣ Serving Tweets ‣
Cassandraã¨HBaseã®æ¯”較ã—ã¦å…¥é–€ã™ã‚‹NoSQL
第10回Cassandra勉強会ã«ã¦ç™ºè¡¨ã—ãŸã‚¹ãƒ©ã‚¤ãƒ‰ã«ã€å‹‰å¼·ä¼šå¾Œã®ãƒ•ã‚£ãƒ¼ãƒ‰ãƒãƒƒã‚¯ã‚’åæ˜ ã•ã›ãŸç‰©ã§ã™ã€‚Read less
NoSQL 時代ã®ãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒ«
Masayoshi Hagiwara @masayh RDBMS対Hadoopã¨ã„ã†æ¯”較自体ã¯é©åˆ‡ã§ã¯ãªã„。æ£ç¢ºã«ã¯ã€RDBMSã¨Hadoopã«ãŠã‘る並列アルゴリズムやデータ管ç†æŠ€è¡“ã®æ¯”較。ã™ã§ã«RDBMSã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã¯ãƒ‡ãƒ¼ã‚¿ç®¡ç†æŠ€è¡“ã¯éžRDBMS化ã—ã¦ã„ã¦ã€ãã‚Œã¯Hadoopã‚„ãã®ä»–ã®NoSQLã«ã‚‚é©ç”¨å¯èƒ½ã¨ãªã£ã¦ã„る。 2010-11-05 14:09:34 Masayoshi Hagiwara @masayh ãŸã¨ãˆã°ã€NoSQLã§ã‚‚スã‚ーマやæ£è¦åŒ–ã®è€ƒãˆæ–¹ã‚’è¨è¨ˆã«å–り入れãŸæ–¹ãŒã„ã„ã—ã€ãれを実装ã«å…¥ã‚Œã¦ã€ç¾åœ¨ã®NoSQLã®æŒã¤ãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒ«ã®å„ªä½æ€§ã‚’æãªã†ã“ã¨ãªã最é©åŒ–ã™ã‚‹ã“ã¨ãŒã§ãã‚‹ã§ã—ょã†ã€‚ 2010-11-05 14:12:20 Masayoshi Hagiwara @masayh 関係代数や関係論ç†ã¨ã„ã£ãŸæŠ€è¡“的基盤をもã£ã¨å‚ç…§ã—ã¦ã€ç¾åœ¨ã®NoSQLã‚„ãã®ä»–ã®ãƒ‡ãƒ¼ã‚¿ç®¡ç†æŠ€è¡“
Why Nobody’s Searching for ‘Big Data’ – Old GigaOm
Matthew Aslett at The 451 Group posted some interesting Google Trends graphs shared with him by Cloudera, showing that searches for “Hadoop†far exceed searches for “big data†or “MapReduce.†He notes that even taking the graphs with a grain of salt, they are a strong validation of interest in Hadoop. However, it might not be necessary to view these trends with that grain of salt. It seems likely
Another NoSQL Comparison: Evaluation Guide
The requirements were clear: Fast data insertion.Extremely fast random reads on large datasets. Consistent read/write speed across the whole data set. Efficient data storage. Scale well.Easy to maintain. Have a network interface.Stable, of course.The list of NoSQL databases to be compared: Tokyo Cabinet, BerkleyDB, MemcacheDB, Project Voldemort, Redis, and MongoDB, not so clear. The methodology to
NoSQL, RDBMS, and The Innovator's Dilemma
I was reading ☞ this post by Mark Suster explaining the innovator’s dilemma, incumbent and new comers behavior in the market. And then I realized that it applies very well to the NoSQL databases market too: Professor Clayton M.Christensen’s, author of The Innovator’s Dilemma, definition: An innovation that is disruptive allows a whole new population of consumers access to a product or service that
NoSQL Is for the Birds – Old GigaOm
Scale breaks everything. Scale even breaks your assumptions about how best to store and query data. Scale does not care about your personal engineering preferences, or about SQL vs. NoSQL. The demands of rapid growth and ever-higher expectations for availability, performance, and cost efficiency force you to re-evaluate and re-imagine what you need, what is possible, and how to best achieve your b
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Amazon.co.jp: ビッグデータをå¾ã™ クラウドã®æŠ€è¡“ Hadoop&NoSQL: ASCII.technologies集部: 本
NoSQL Benchmark Source Code Available
NoSQLデータベースãŒç™»å ´ã—ãŸèƒŒæ™¯ã¨ç‰¹å¾´
Amazon.co.jp: Professional NoSQL: Tiwari, Shashank: 本
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