Database System Implementation
Revised Edition Available Oct. 1, 2001 This book has been replaced by a larger book, Database Systems: The Complete Book, which includes updated material from this book and A First Course in Database Systems. Click here: for more information. Index Solutions to Selected Exercises Errata Slides Course Notes Book-Ordering Information The book Database System Implementation by Hector Garcia-Molina, J
第1回 記憶装置のトレードオフとバッファの考え方―すべてをとることができないとき （2） | gihyo.jp
DBMSと記憶装置の関係 DBMSは重要なデータを保存することを第一の目的としたミドルウェアですから、記憶装置とは切っても切れない関係にあります。 DBMSがデータを保存する媒体は、ほぼ100％、ハードディスクです。ディスク以外の選択肢がまったくない、というわけではないのですが[1]、ほとんどの場合においては、容量、コスト、パフォーマンスなどの総合的な観点から、ハードディスクが選択されています。 ハードディスクは、記憶装置の階層でいうと真ん中の二次記憶装置に分類されます。これはつまり、とても良いところがない代わりに、大きな欠点もない媒体ということです。データベースは、冒頭でも言ったように、ほとんどのシステムで利用されている汎用的なミドルウェアですから、平均的な媒体が選択されているのは自然なことです。 しかしそれは、DBMSがデータをディスク以外に持っていない、ということを意味するわけでは
ActorDB | Distributed SQL database with linear scalability
Features ActorDB is strongly consistent, distributed and horizontally scalable. Based on an industry-proven reliable database engine. Scalable ActorDB can run on a single server or hundreds. It can store gigabytes or petabytes. Features Full relational database within an actor. Queries and transactions over multiple actors. Redundant. Massively concurrent. No single point of failure. ACID. Connect
MyRocks Performance
In this blog post, I’ll look at MyRocks performance through some benchmark testing. As the MyRocks storage engine (based on the RocksDB key-value store http://rocksdb.org ) is now available as part of Percona Server for MySQL 5.7, I wanted to take a look at how it performs on a relatively high-end server and SSD storage. I wanted to check how it performs for different amounts of available memory f
スタンフォードの授業でデータベースの英語を勉強する - きしだのはてな
「Database Management Systems」を読み始めたので、英語に慣れるためにスタンフォードのデータベースの授業を見ようかと思った。 Algebraとか、なかなか音で聞く機会がないので、なじむのにいいかと。 http://www.db-class.org/course/video/preview_list スタンフォードといっても、内容はデータベースの基礎なんで、リレーショナルモデルとか内容自体はそんなに難しくない。 右下の噴出しをクリックすると、英語字幕が出るので、文字と音の対応もつけやすい。面白いのは、1.5倍速という精神と時の部屋モードがあること。ちょっと機械っぽくはあるんだけど、これに慣れると通常の速さが聞き取りやすくなるし、10分聞けば下界の15分の勉強に相当する。 ところで、「Database Management Systems」は、インデックスやクエリー評価
Architecture of a Database System
Foundations and Trends R � in Databases Vol. 1, No. 2 (2007) 141–259 c � 2007 J. M. Hellerstein, M. Stonebraker and J. Hamilton DOI: 10.1561/1900000002 Architecture of a Database System Joseph M. Hellerstein1 , Michael Stonebraker2 and James Hamilton3 1 University of California, Berkeley, USA, hellerstein@cs.berkeley.edu 2 Massachusetts Institute of Technology, USA 3 Microsoft Research, USA Abstra
Dynamo and BigTable - Review and Comparison
Presentation from the IEEE 28th Convention of Electrical & Electronics Engineers in Israel (IEEEI), 2014
Self-Driving Databases: Current and Future - Treasure Data Blog
Self-Driving Databases: Current and Future Last modified: April 6, 2020 Treasure Data is a fully-managed DBMS service that frees our customers from operating DBMS by themselves. This empowers non-engineers (e.g., executives, marketers, etc.) to collect data and get insights through data analysis in a self-service manner. In October 2017, Oracle unveiled the world-first self-driving database as a s
SIGMOD 2018 Accepted Papers
Here is the list of accepted papers for SIGMOD 2018. I’ve attached links to PDFs to some of the papers of my interest if they are already available on the web. The 2018 ACM SIGMOD/PODS Conference: Houston, USA - SIGMOD Accepted Research Papers Fonduer: Knowledge Base Construction from Richly Formatted Data Sen Wu (Stanford University); Luke Hsiao (Stanford… Research PapersCold Filter: A Meta-Frame
PipelineDB—The Streaming SQL Database
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The last decade of database research and its blindingly bright future. or Database Research: A love song. · Stanford DAWN
The last decade of database research and its blindingly bright future. or Database Research: A love song. by Michael Cafarella and Chris Ré 11 Apr 2018 To go by Twitter and many hallway conversations, the database research community has been unsettled lately in a way that we have never seen before. Many people are unhappy with the review process, many types of useful work seem to be more difficult
FoundationDB is Open Source
Published April 19, 2018The next chapterStarting today, FoundationDB starts its next chapter as an open source project! FoundationDB is a distributed datastore, designed from the ground up to be deployed on clusters of commodity hardware. These clusters scale well as you add machines, automatically heal from hardware failures, and have a simple API. The key-value store supports fully global, cross
Using Prepared Statements
Prepared statements have all the usual benefits in Go: security, efficiency, convenience. But the way they’re implemented is a little different from what you might be used to, especially with regards to how they interact with some of the internals of database/sql. Prepared Statements And Connections At the database level, a prepared statement is bound to a single database connection. The typical f
Titan: Distributed Graph Database
Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. In addition, Titan provides the following features: Elastic and linear scalability for a growin
The Case for Learned Index Structures
The Google-brewed paper has thought-provoking ideas and is poised to be remembered for a long time. The paper’s key question is: can indexing data structures (e.g. B-Trees or HashMaps) be replaced with machine learning models (e.g. Neural Networks) ? (Figure 1). Indexes as predictive modelsThis simple question completely broke mine and others’ previous idea of what an index is: Before: indexes ==
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Improving Write Performance of LSMT-Based Key-Value Store
Readings in Database Systems, 5th Edition
Fall 2023 CS262a: Course Schedule and Lectures
CS 564, Spring 2017
365日24時間稼働必須サービスの 完全無停止DB移行
