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，并且在许多方面将继续是数据革命背后的主要驱动引擎。这些系统的特点是相对高效，强大，优雅，声明式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。这一交易使得编写大范围的大型数据应用程序变得容易得多，但当然，这一交易也伴随着成本。一个局限于“查询语言”接口（如SQL和Xquery）提供的内容。虽然SQL已经发展成为一个非常适合关系数据管理和支持业务应用程序的复杂分析查询的平台，但具有不小的讽刺意味的是，它不适合数据探索和可视化任务。与此同时，探索和可视化的大型数据集已经成为今天一样重要的需要已经是传统的数据管理在过去。我们计划提供一个无尺度的，渐进的，直接可视化的聚合数据的类型的SQL查询支持数据探索。

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.