UC Berkeley

Spreadsheet software is often the tool of choice for ad-hoc tabular data management, processing, and visualization, especially on tiny data sets. On the other hand, relational database systems offer significant power, expressivity, and efficiency over spreadsheet software for data management, while lacking in the ease of use and ad-hoc analysis capabilities. We demonstrate DataSpread, a data exploration tool that holistically unifies databases and spreadsheets. It continues to offer a Microsoft Excel-based spreadsheet front-end, while in parallel managing all the data in a back-end database, specifically, PostgreSQL. DataSpread retains all the advantages of spreadsheets, including ease of use, ad-hoc analysis and visualization capabilities, and a schema-free nature, while also adding the advantages of traditional relational databases, such as scalability and the ability to use arbitrary SQL to import, filter, or join external or internal tables and have the results appear in the spreadsheet. DataSpread needs to reason about and reconcile differences in the notions of schema, addressing of cells and tuples, and the current "pane" (which exists in spreadsheets but not in traditional databases), and support data modifications at both the front-end and the back-end. Our demonstration will center on our first and early prototype of the DataSpread, and will give the attendees a sense for the enormous data exploration capabilities offered by unifying spreadsheets and databases.