Building data visualization and exploration support into an embedded database system: Big Data in the small

关系数据库系统一直是，而且在许多方面将继续是数据革命背后的主要驱动引擎。实现这场革命的这些系统的特点是相对高效、强大、优雅的声明性查询语言和事务一致性。Codd的数据独立性原则提供了一个抽象层，允许应用程序和用户在逻辑级别处理数据，而不需要知道数据库系统如何在物理级别处理数据。数据独立性允许数据库引擎确保事务一致性；这消除了应用程序这样做的需要。这笔交易使得编写范围广泛的大型数据应用程序变得非常容易。但当然，这种交易也伴随着成本。其中之一仅限于“查询语言”接口(如SQL和XQuery)提供的内容。虽然SQL已经发展成为一个相当胜任的平台，用于关系数据管理和支持业务应用程序的复杂分析查询，但具有讽刺意味的是，它不太适合数据探索和可视化任务。同时，大数据集合的探索和可视化在今天变得与过去的传统数据管理一样重要。我们计划为支持数据探索的SQL查询类型提供无标度、渐进式、直接的聚集数据可视化。

Relational database systems have been, and in many ways continue to be, the main driving engine behind thedata revolution. The hallmarks of these systems that enabled the revolution are relative efficiency, powerful,elegant, declarative query languages, and transactional consistency.Codd's Principle of Data Independence provided for a layer of abstraction that has allowed applications andusers to deal with the data at a logical level, without need to know how the database system deals with the dataat the physical level. Data independence allows for the database engine to ensure transactional consistency; thisremoves the need for application programs to do so. This bargain has made writing a wide range of large dataapplications significantly easier.But this bargain does come with costs too, of course. One is limited to what the "query-language" interfaces,such as SQL and Xquery, provide. While SQL has evolved into a quite competent platform for relational datamanagement and for complex analytic queries backing business applications, it is, with no small irony, poorlysuited for data exploration and visualization tasks. Meanwhile, exploration and visualization of large datacollections has become just as important a need today as has been traditional data management in the past.We plan to provide a scale-free, progressive, direct visualization of aggregate data for types of SQL queriestowards supporting data exploration.