poloclub.github.io/#cse6242
 CSE6242/CX4242: Data & Visual Analytics
 Simple Data Storage; SQLite Duen Horng (Polo) Chau
 Associate Professor, College of Computing
 Associate Director, MS Analytics
 Faloutsos How to store the data?
 What’s the easiest way? Easiest Way to Store Data As comma-separated files (CSV) But may not be easy to parse. Why? 3 Easiest Way to Store Data 4 https://en.wikipedia org/famous.html
 iPhone (iOS), Android, Chrome (browsers), Mac, etc. Self-contained: one file contains data + schema Serverless: database right on your computer Zero-configuration: no need to set up! See

1 Table of Contents Chapter 1 - Introduction 4 About Navicat Data Modeler 4 Installation 5 Registration 6 Migration / Upgrade 7 End-User License Agreement 7 Chapter 2 - User Interface Trace Logs 84 Log Files 84 4 Chapter 1 - Introduction About Navicat Data Modeler Navicat Data Modeler is a powerful and easy-to-use GUI tool for creating and manipulating database models print models to files, etc. Navicat Data Modeler is available on three platforms - Microsoft Windows, macOS and Linux. Here are some highlights of Navicat Data Modeler: • Create and manipulate c

1 Table of Contents Chapter 1 - Introduction 4 About Navicat Data Modeler 4 Installation 5 Registration 5 Migration / Upgrade 6 End-User License Agreement 7 Chapter 2 - User Interface Trace Logs 82 Log Files 82 4 Chapter 1 - Introduction About Navicat Data Modeler Navicat Data Modeler is a powerful and easy-to-use GUI tool for creating and manipulating database models print models to files, etc. Navicat Data Modeler is available on three platforms - Microsoft Windows, macOS and Linux. Here are some highlights of Navicat Data Modeler: • Create and manipulate c

Unified Data Layers: A New Era for Scalable Analytics, Search, and AI v 1.1Table of Contents Introduction 1. The Interconnection of Analytics, Search, and AI 2. What is a Real-Time Unified Data Layer Layer? 3. Why Do You Need a Real-Time Unified Data Layer? 4. 5.CrateDB: A Modern Real-Time Unified Data Layer1. Introduction Data teams are facing more challenges than ever. As applications generate and and consume unprecedented volumes of data across a growing number of sources and formats, data engineering and architecture teams must design systems that not only scale but also deliver real-time access

阿里云 AnalyticDB for PostgreSQL - 打造更简单易用的Cloud SQL Data Warehouse 个人介绍 缪长风 ⚫ 2010年初加入支付宝，负责Oracle RAC和Greenplum数据仓库 ⚫ 有幸参与了Oracle RAC到 Greenplum再到Hadoop以及最终到 ODPS的架构演进工作。 ⚫ 2012年起，转至阿里巴巴大数据团队，负责Hbase/OTS业务支 RDS 关系型数据 库D ECS自建 自建大数据计算平台 Hadoop Spark EMR Dataphi n OSS海量云存储 Data Lake Store DTS 实时同步 Dump Data Dump Data 数据集成 按需回流 数据仓库应用 在线数据仓库 数据 查询 数据集成 批量同步 1 3 4 2 云化在线数仓 ： 简化、敏捷、一栈式构筑数据仓库

.............................................................................. 24 Protecting your data ................................................................................................. a database file can copy it, install it on a system under his or her own control, and extract all data from it – including possibly sensitive information. Anybody who has filesystem-level write access Aliases are listed in the file aliases.conf, in this format on Windows machines: poker = E:\Games\Data\PokerBase.fdb blackjack.fdb = C:\Firebird\Databases\cardgames\blkjk_2.fdb And on Linux: books =

security assessment targeting the Vitess software database scaler. Funded by the CNCF / The Linux Foundation, this project was carried out by Cure53 in February 2019 and revealed only three miscellaneous database. In particular, the possibility of breaking out of strings by providing legitimately escaped data was attempted but no vulnerabilities could be spotted. • Interesting behaviors, such as the comment potentially resides in string values of SQL statements This might lead to the leakage of sensitive user-data whenever the debug interfaces of Vitess are opened. In MySQL, strings are usually encapsulated by

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 7. Protecting your data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . access to a database file can copy it, install it on a system under their own control, and extract all data from it — including possibly sensitive information. Anybody who has filesystem-level write access own filesystem space and make embedded connections to them. Since these are their files and their data, one may argue that unrestricted and possibly destructive access should be their own concern, not

杭州拓数派科技发展有限公司（又称"OpenPie"）是立足于国内,基础数据计算领域的高科技创新机构。 作 为 国 内 云 上 数 据 库 和 数 据 计 算 领 域 的 引 领 者 ， 拓 数 派 以 “Data Computing for New Discoveries”「数据计算，只为新发现」为使命，致力于在数字原生时代,运用突破性计算理论、 独创的云原生数据库旗舰产品以及之上的算法和数学模型,建立下一代云原生数据平台的前沿标准 Maritz（届时VMware CEO，曾任微软Windows平台总负责人）和Scott Yara的支持下创建了Pivotal中国。 卡内基梅隆大学 (CMU)上海校友会主席、1024Foundation 创始人 冯雷 Ray Von • 以浙江物理奥赛银牌进入北大物理学院，在北大彼时“理科实验班”(现元培项目）浸染在数学、物理、 计算机和经济学，获得物理经济学双学位。（北大报道）研 Greenplum数据库（中国）创始人 大数据意见领导者 h t m 5 1 1 20 2 2 45 3 2 80 4 1 125 5 2 180 6 2 数 据 计 算 ， 只 为 新 发 现 (Data Computing for New Discoveries) • 全新云原生架构「一份数据，多引擎计算」 弹 性 扩 缩 容 ， 打 破 数 据 孤 岛 • 全 面 支 持

Apache!Cassandra,!Apache!Hadoop,!Hadoop!and!the!eye!logo! are!trademarks!of!the!Apache!Software!Foundation! Contents Apache Cassandra 1.0 Documentation 1 Introduction to Apache Cassandra 1 Getting Started Cassandra 1 Create a Keyspace (database) 1 Create a Column Family 2 Insert, Update, Delete, Read Data 2 Getting Started with Cassandra and DataStax Community Edition 2 Installing a Single-Node Instance Application 6 About the Portfolio Demo Use Case 6 Running the Demo Web Application 6 Exploring the Sample Data Model 7 Looking at the Schema Definitions in Cassandra-CLI 8 DataStax Community Release Notes 8