マãƒãƒ¼ã‚¸ãƒ‰ã‚°ãƒ©ãƒ•ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ - Amazon Neptune - AWS
Neptune ãŒé¸ã°ã‚Œã‚‹ç†ç”± Neptune ã¯ã‚°ãƒ©ãƒ•ãƒ¯ãƒ¼ã‚¯ãƒãƒ¼ãƒ‰ã‚’å³åº§ã«ã‚¹ã‚±ãƒ¼ãƒ«ã™ã‚‹ãŸã‚ã€ã‚ャパシティを管ç†ã™ã‚‹å¿…è¦ãŒãªããªã‚Šã¾ã™ã€‚データをグラフã¨ã—ã¦ãƒ¢ãƒ‡ãƒ«åŒ–ã™ã‚‹ã“ã¨ã§ã€Neptune ã¯ã‚³ãƒ³ãƒ†ã‚ストをæ‰ãˆã€ç”Ÿæˆ AI アプリケーションã®ç²¾åº¦ã¨èª¬æ˜Žå¯èƒ½æ€§ã‚’å‘上ã•ã›ã¾ã™ã€‚AI アプリケーションã®é–‹ç™ºã‚’容易ã«ã™ã‚‹ãŸã‚ã«ã€Neptune ã§ã¯ Amazon Bedrock ナレッジベースを備ãˆãŸãƒ•ãƒ«ãƒžãƒãƒ¼ã‚¸ãƒ‰åž‹ã® GraphRAG ã¨ã€Strands AI Agents SDK ãŠã‚ˆã³ä¸€èˆ¬çš„ãªã‚¨ãƒ¼ã‚¸ã‚§ãƒ³ãƒˆå‘ã‘メモリツールã¨ã®çµ±åˆã‚’æä¾›ã—ã¦ã„ã¾ã™ã€‚ã¾ãŸã€æ§‹é€ 化データã¨éžæ§‹é€ 化データã«ã¾ãŸãŒã‚‹æ•°ç™¾å„„ã®ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒ³ã‚·ãƒƒãƒ—を数秒ã§ç°¡å˜ã«åˆ†æžã—ã€æˆ¦ç•¥çš„ãªã‚¤ãƒ³ã‚µã‚¤ãƒˆã‚’æä¾›ã—ã¾ã™ã€‚Neptune ã¯ã€ã‚³ãƒã‚¯ãƒ†ãƒƒãƒ‰ãƒ‡ãƒ¼ã‚¿ã®åŠ›ã‚’ AWS ã®ã‚¨ãƒ³ã‚¿ãƒ¼ãƒ—ライズ機能ãŠã‚ˆã³ä¾¡å€¤ã¨å…±ã«æ´»ç”¨ã§ãã‚‹ã€å”¯ä¸€ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã§
Amazon Timestream
Amazon Timestream for LiveAnalytics ã«é¡žä¼¼ã™ã‚‹æ©Ÿèƒ½ã«ã¤ã„ã¦ã¯ã€Amazon Timestream for InfluxDB ã‚’ã”検討ãã ã•ã„。リアルタイム分æžã®ãŸã‚ã«ã€ç°¡ç´ 化ã•ã‚ŒãŸãƒ‡ãƒ¼ã‚¿ã‚¤ãƒ³ã‚¸ã‚§ã‚¹ãƒˆã¨ã€1 æ¡ãƒŸãƒªç§’ã®ã‚¯ã‚¨ãƒªå¿œç”時間をæä¾›ã—ã¾ã™ã€‚詳細ã«ã¤ã„ã¦ã¯ã“ã¡ã‚‰ã‚’ã”覧ãã ã•ã„。 Amazon Timestream ã¯ã€ä½Žãƒ¬ã‚¤ãƒ†ãƒ³ã‚·ãƒ¼ã®ã‚¯ã‚¨ãƒªã‹ã‚‰å¤§è¦æ¨¡ãªãƒ‡ãƒ¼ã‚¿ã‚¤ãƒ³ã‚¸ã‚§ã‚¹ãƒˆã¾ã§ã®ãƒ¯ãƒ¼ã‚¯ãƒãƒ¼ãƒ‰ã«å¯¾å¿œã™ã‚‹ã€å®Œå…¨ãƒžãƒãƒ¼ã‚¸ãƒ‰åž‹ã®å°‚用時系列データベースエンジンをæä¾›ã—ã¾ã™ã€‚Amazon Timestream for LiveAnalytics を利用ã™ã‚‹ã¨ã€1 分ã‚ãŸã‚Šæ•°å GB を超ãˆã‚‹æ™‚系列データをå–ã‚Šè¾¼ã¿ã€TB è¦æ¨¡ã®æ™‚系列データã«å¯¾ã—㦠SQL クエリを数秒ã§å®Ÿè¡Œã§ãã‚‹ã»ã‹ã€æœ€å¤§ 99.99% ã®å¯ç”¨æ€§ã‚’実ç¾ã§ãã¾ã™ã€‚時系列分æžé–¢æ•°ãŒçµ„ã¿è¾¼ã¾ã‚Œã¦ãŠã‚Šã€ã»ã¼ãƒª
Amazon QLDB
Amazon Aurora Unparalleled high performance and availability at global scale for PostgreSQL, MySQL, and DSQL Aurora has 5x the throughput of MySQL and 3x of PostgreSQL with full PostgreSQL and MySQL compatibility. Aurora also offers DSQL, the fastest distributed SQL database that is PostgreSQL-compatible. Aurora is designed for up to 99.999% multi-Region availability. With Aurora DSQL, Aurora prov
SELECTã—ãŸçµæžœã‚’使ã£ã¦ã€CREATE TABLEã™ã‚‹ - on the center line.
一時的ã«ãƒ‡ãƒ¼ã‚¿ã‚’退é¿ã—ã¦ãŠãã¨ãã«ã€SELECTã—ãŸçµæžœã‚’ãã®ã¾ã¾ãƒ¯ãƒ¼ã‚¯ãƒ†ãƒ¼ãƒ–ルã«ã¶ã¡ã“ã¿ãŸãã¦èª¿ã¹ã¦ã¿ãŸã‚‰ã€çµæ§‹ç°¡å˜ã«ã§ãã‚‹ã‚“ã§ã™ã。複数ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã«å¯¾å¿œã—ãŸã‹ã£ãŸã®ã§ã€å„データベースã«ã¤ã„ã¦èª¿ã¹ã¦ã¿ãŸã¨ã“ã‚ã€å¤§ä½“åŒã˜ã‚ˆã†ãªSQLã§ã§ãã‚‹ã¿ãŸã„ã§ã—ãŸã€‚ [MySQL] create table table_name (select * from other_table) [Oracle] create table table_name as select * from other_table [SQLServer] select * into table_name from other_table ※Postgreã§ã‚‚ãã£ã¨ã§ãã‚‹ã¨æ€ã„ã¾ã™ãŒã€èª¿æŸ»ã—ã¦ã¾ã›ã‚“。
PostgreSQLã§ãƒ†ã‚¹ãƒˆãƒ‡ãƒ¼ã‚¿ã‚’作æˆã™ã‚‹ | Let's POSTGRES
ç¬ åŽŸ è¾°ä» æœ¬è¨˜äº‹ã¯2013å¹´ã®PostgreSQL Advent Calendar ã® 12/25 ã®è¨˜äº‹ã§ã™(地味ãªãƒˆãƒ”ックã«ãªã£ã¦ã—ã¾ã„ã™ã„ã¾ã›ã‚“)。PostgreSQLã§ã®ãƒ†ã‚¹ãƒˆãƒ‡ãƒ¼ã‚¿ä½œæˆã«å½¹ç«‹ã¤æ©Ÿèƒ½ã‚’紹介ã—ã¾ã™ã€‚ ã¯ã˜ã‚ã« PostgreSQLを対象ã¨ã—ãŸã®æ€§èƒ½æ¤œè¨¼ã‚„機能検証を行ã†éš›ã«ã€é–‹ç™ºç’°å¢ƒã‚„試験環境ã§ã‚¹ã‚ーマ(テーブルやインデックス)を作æˆã—ã€ãƒ€ãƒŸãƒ¼ã®ãƒ‡ãƒ¼ã‚¿ã‚’投入ã—ã¦SQLã®ãƒã‚§ãƒƒã‚¯ã‚’è¡Œã†ã“ã¨ãŒå¤šã€…ã‚ã‚‹ã‹ã¨æ€ã„ã¾ã™ã€‚å˜ç´”ãªæ©Ÿèƒ½ã®æ£å¸¸è©¦é¨“ã§ã‚ã‚Œã°å°‘é‡ã®ãƒ‡ãƒ¼ã‚¿æŠ•å…¥ã§äº‹è¶³ã‚Šã‚‹ã¨æ€ã„ã¾ã™ãŒã€å¤§é‡ã®ãƒ‡ãƒ¼ã‚¿ã«å¯¾ã™ã‚‹æ¤œç´¢å‡¦ç†ã‚„ãƒãƒƒãƒå‡¦ç†ã‚’試ã™éš›ã¯ã€ãã‚Œãªã‚Šã®é‡ã®è©¦é¨“データを生æˆã—ã€DBã«æŠ•å…¥ã™ã‚‹å¿…è¦ãŒã‚ã‚Šã¾ã™ã€‚ 通常ã€è©¦é¨“データã¯ã€ä¾‹ãˆã°å°‚用ã®ã‚¸ã‚§ãƒãƒ¬ãƒ¼ã‚¿ã‚’作るã€å®Ÿéš›ã®ãƒ‡ãƒ¼ã‚¿ã‚’マスã‚ングã—ãŸã‚‚ã®ã‚’使ã†ã€ã‚µãƒ³ãƒ—ルã¨ã—ã¦å˜åœ¨ã™ã‚‹ãƒ‡ãƒ¼ã‚¿(郵便番å·ã®ãƒ‡ãƒ¼ã‚¿ãªã©)を利用ã™ã‚‹ã€ã¨ã„ã£ãŸã“ã¨ãŒå¤šã„ã¨æ€
TrailDB
Maximize Speed TrailDB is a library, implemented in C, which allows you to query series of events at blazing speed. TrailDB is also optimized for speed of development: Use its simple API with your favorite language, in your favorite environment. Minimize Space TrailDB's secret sauce is data compression. It leverages predictability of time-based data to compress your data to a fraction of its origi
PostgreSQLã¨MySQLã€ä½¿ã†ãªã‚‰ã©ã£ã¡ï¼Ÿ データベース専門家ãŒ8ã¤ã®è¦–点ã§å¾¹åº•æ¯”較ï¼ï½œãƒã‚¤ã‚¯ãƒ©ã‚¹è»¢è·ãƒ»æ±‚äººæƒ…å ±ã‚µã‚¤ãƒˆ AMBI（アンビ）
PostgreSQLã¨MySQLã€ä½¿ã†ãªã‚‰ã©ã£ã¡ï¼ŸÂ データベース専門家ãŒ8ã¤ã®è¦–点ã§å¾¹åº•æ¯”è¼ƒï¼ ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã¨ã—ã¦ã‚ˆã比較ã•ã‚Œã‚‹PostgreSQLã¨MySQL。ã©ã‚“ãªé•·æ‰€ãƒ»çŸæ‰€ãŒã‚ã‚‹ã®ã§ã—ょã†ï¼ŸÂ ãã‚Œãžã‚Œã®å°‚門家ã«ã‚ˆã‚‹å¯¾è«‡ã§æ˜Žã‚‰ã‹ã«ã—ã¾ã™ã€‚ エンジニアã¨ã—ã¦åƒã„ã¦ã„ã‚‹ã¨å¿…ãšç›´é¢ã™ã‚‹æ‚©ã¿ã€‚ãã‚Œã¯ã€ã€Œã©ã®ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãƒ»ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ï¼ˆä»¥ä¸‹ã€RDB）をé¸ã¶ã®ãŒæœ€å–„ãªã®ã‹ï¼Ÿã€ã§ã™ã€‚ RDBã”ã¨ã«é•·æ‰€ã¨çŸæ‰€ã¯ç•°ãªã£ã¦ã„ã¾ã™ã€‚ãã®ãŸã‚自社サービスã«ãƒžãƒƒãƒã—ãªã„RDBã‚’é¸ã‚“ã§ã—ã¾ã†ã¨ã€ãã‚ŒãŒãƒœãƒˆãƒ«ãƒãƒƒã‚¯ã¨ãªã‚Šé–‹ç™ºãƒ»é‹ç”¨ã«ãƒˆãƒ©ãƒ–ルãŒç”Ÿã˜ã‚‹ã‚±ãƒ¼ã‚¹ã¯å°‘ãªãã‚ã‚Šã¾ã›ã‚“。 ãªã‹ã§ã‚‚よã比較検討ã•ã‚Œã‚‹ã®ãŒã€PostgreSQLã¨MySQL。ã¨ã‚‚ã«ã‚ªãƒ¼ãƒ—ンソースRDBã®ãƒ‡ãƒ•ã‚¡ã‚¯ãƒˆã‚¹ã‚¿ãƒ³ãƒ€ãƒ¼ãƒ‰ã§ã‚ã‚Šã€é«˜ã„性能ã¨æ•°å¤šãã®æ©Ÿèƒ½ã‚’æŒã£ã¦ã„ã¾ã™ã€‚ ã§ã¯ã€ä¸¡è€…ã¯å…·ä½“çš„ã«ã©ã®ã‚ˆã†ãªé•·æ‰€ãƒ»çŸæ‰€ãŒã‚ã‚‹ã®ã§ã—ょã†ã‹ã€‚ã
Client Failover Best Practices for Highly Available Oracle Databases: Oracle Database 11g Release 2
NoSQL and SQL Introspective Oracle NoSQL Database 11g Release 2 (11.2.1.2) Oracle White Paper October 2013 Oracle NoSQL Database Oracle White Paper— NoSQL and SQL Introspective: Oracle NoSQL Database 11g Release 2 Introduction ....................................................................................... 2 NoSQL – purpose-built data management......................................... 2 No
Apache Spark ã® JdbcRDD を使ã£ã¦ã¿ãŸçµæžœ - Qiita
package sample import java.sql.{Connection, DriverManager, ResultSet} import org.apache.spark.SparkContext import org.apache.spark.SparkConf import org.apache.spark.rdd.JdbcRDD object Invastigation { def main(args: Array[String]): Unit = { val conf = new SparkConf().setAppName("Invastigation") val context = new SparkContext(conf) val dbDriver = "com.mysql.jdbc.Driver" val dbUrl = "jdbc:mysql://loc
MySQLæ–‡å—列型“varchar(255)â€ã¨â€œvarchar(256)â€çµå±€ã©ã£ã¡ãŒè‰¯ã„?
押å¿ï¼ dice（@dice_dDtea）ã§ã™ã€‚ varchar型を使ã†ã¨ã〠指定ã™ã‚‹æ•°å—ã¯ã„ãã¤ãŒã„ã„ã®ã ã‚ã†ã‹ï¼Ÿ 調ã¹ã¦ã‚‹ã¨ã€Œ255ã€ã¨ã€Œ256ã€ã‚’よãç›®ã«ã™ã‚‹ã€‚ varchar(255) 㨠varchar(256) ã§ã©ã£ã¡ã‚’使ã†ã»ã†ãŒè‰¯ã„ã‹è«–争もã‚ã‚‹ãらã„ã 。 『MySQLã®VARCHARサイズã«ã¤ã„㦠– Togetterã¾ã¨ã‚〠http://togetter.com/li/54358 UTF-8ã§255ã‹256ã‹ã®ã¨ã“ã‚ã«ã‚ªãƒ¼ãƒãƒ¼ãƒ•ãƒãƒ¼ãƒšãƒ¼ã‚¸åˆ©ç”¨æœ‰ç„¡ã®å¢ƒç›®ãŒã‚ã‚Šã¾ã™ã€‚ http://bit.ly/94z5BV RT @sugyan: 255ã§ã‚‚256ã§ã‚‚パフォーマンス的ã«å¤§ããªé•ã„ã¯ãªã„ã¨æ€ã†ã®ã ã‘ã© ãªã‚“ã‹ã€Œã“ã†ã„ã†ç†ç”±ã§ã“ã£ã¡ã‚’é¸ã¶ã‚“ã よï¼ã€ã¿ãŸã„ã®ãŒæ¬²ã— — SH2 (@sh2nd) 2010, 9月 27 今回ã“ã®çµè«–を出ã—ã¦è¦‹ãŸã„ã¨æ€ã†ã€‚ 「255ã€ã¨ã€Œ256ã€
æ•´æ•°åž‹ - MySQLã®ãƒ‡ãƒ¼ã‚¿åž‹ - MySQLã®ä½¿ã„æ–¹
MySQL ã§åˆ©ç”¨å¯èƒ½ãªãƒ‡ãƒ¼ã‚¿åž‹ã®ä¸ã§æ•´æ•°åž‹(TINYINT, SMALLINT, MEDIUMINT, INT, BIGINT)ã®ä½¿ã„æ–¹ã«ã¤ã„ã¦è§£èª¬ã—ã¾ã™ã€‚ TINYINT[(M)] [UNSIGNED] [ZEROFILL] 符å·ä»˜ãã®ç¯„囲㯠-128 ã‹ã‚‰ 127 。符å·ãªã—ã®ç¯„囲㯠0 ã‹ã‚‰ 255 。 SMALLINT[(M)] [UNSIGNED] [ZEROFILL] 符å·ä»˜ãã®ç¯„囲㯠-32768 ã‹ã‚‰ 32767 。符å·ãªã—ã®ç¯„囲㯠0 ã‹ã‚‰ 65535 。 MEDIUMINT[(M)] [UNSIGNED] [ZEROFILL] 符å·ä»˜ãã®ç¯„囲㯠-8388608 ã‹ã‚‰ 8388607 。 符å·ãªã—ã®ç¯„囲㯠0 ã‹ã‚‰ 16777215 。 INT[(M)] [UNSIGNED] [ZEROFILL] 符å·ä»˜ãã®ç¯„囲㯠-2147483648 ã‹ã‚‰ 2147483647
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Java Database - 2.3.x
PostgreSQLã§MySQLã®ã‚ˆã†ãªAUTO_INCREMENTã‚’ã—ãŸã„ã¨ã。 – ã“ã¨ã¨ã“ãƒãƒƒãƒˆ
Redash Help Center
MySQLã¨PotgreSQLã®ãƒ¬ãƒ—リケーション比ã¹ã¦ã¿ãŸ
Aerospike | Aerospike
https://db-engines.com/en/system/Cassandra%3BHBase%3BOracle+NoSQL
What is the difference between tinyint, smallint, mediumint, bigint and int in MySQL?
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