Dabble DB Bridges Database, Spreadsheet Divide
Dabble DB Bridges Database, Spreadsheet Divide
Dabble DB is a Web-based application from Smallthought Systems that can help solve one of the modern knowledge worker's most enduring dilemmas by bridging the gap between the spreadsheet and the database.
Spreadsheet applications are excellent tools for ad hoc data crunching. You fire up a new spreadsheet, key or paste in your data and then sort, filter and formulate your way to data analysis enlightenment. Things can turn ugly, however, as those ad hoc spreadsheets put down roots and grow into de facto applications that would be better implemented as databases.
Unfortunately, the structured nature of databases, which requires a lot of planning ahead, tends to mesh poorly with the open-ended mindset of the typical spreadsheet user, resulting in deepening roots for those overloaded spreadsheets.
Enter the aptly named Dabble DB, which combines the structured data entry, distribution and access benefits of databases without surrendering the open-ended usage traits that spreadsheet dabblers prize.
Dabble DB does a good job of importing data and makes it very easy for users to create views of the tables (called "categories" in Dabble parlance) in which their data resides. It's also easy to change the schema of those categories-adding or removing fields and reconfiguring their data types.
The Web-based service won't do everything that a spreadsheet will. For instance, while it's easy to create views that include basic mathematical or text operations, Dabble DB lacks most of the formulas that spreadsheets offer. Given the product's excellent export and import functions, however, Dabble DB can serve well as a complement to your local spreadsheet applications.
For my tests, I focused most directly on the product in its spreadsheet-adjunct role. However, Dabble DB's easy form creation, multiple user support and table relationship capabilities merit evaluation of the product for light database duty, particularly for small organizations with geographically dispersed users.
Dabble DB is priced at $8 per user per month, with a free 30-day trial. There's also a free option for data that's made publicly available under a Creative Commons license. For more pricing information, click here. Holders of paid (or trial) accounts can access their Dabble DB applications over an SSL [Secure Sockets Layer]-encrypted connection.
Users of the service can download a copy of the categories stored on the Dabble servers in the form of comma-separated value-formatted text files, and Dabble takes periodic snapshots of the applications to which users can restore through the service's admin console. It's also possible to trigger application snapshots manually through the same console.
I was underwhelmed by Dabble DB's health status update facilities, which are limited to blog, Twitter and user forum posts following service interruptions or slowdowns. I would prefer to see a dedicated status page for the service.
Dabble DB in Action
I put Dabble DB to the test with some of my most vital data-stats and standings from my fantasy basketball league.
I wanted a solution that required less attention to plumbing than the spreadsheet I was using, and this is just what Dabble DB provided.
I began the process by importing the daily league stats into Dabble via cut and paste. The stats source I use comes formatted in fixed-width format, which is easy to import into Excel or Calc, but which Dabble DB was unable to accept. As a result, I had to first import my source into Calc and then select and paste the table of data to paste into Dabble DB.
Next, Dabble DB gave me a preview of my imported data, and asked if I wished to use the first row of the table as the column headers, which I did. Also at this point, I could see the data types that Dabble had guessed for my imported data.
With my data imported into a new category within my application, Dabble dropped me off at its view creation interface, from which I could select which columns of data I wished to include in the view and begin transforming the data in those columns in a number of ways.
For instance, to calculate field goals made per game, I clicked on the "field goals-made" column and chose, through a series of nested menus, to divide the field goals-made column by the "games-played" column. Dabble added a new column to my view to hold the new information. I could then remove field goals made from the view, and continue adding columns, performing operations on them and dismissing the unneeded columns.
When building future views, I could reference my derived columns, such as field goals made per game, in any other view within my application.
I needed to extend my database schema to include the fantasy league team, if any, to which the players in my data set belonged, and I was able to add this field while creating my view. I first set the data type for the field as text, but later, after I had entered the correct fantasy team values, I switched the data type to list, and was pleased to see that Dabble DB created the list automatically from the existing values in my data.
I was able to access the data in each of my views very flexibly, with HTTP links to my data in RSS, Excel, CSV (comma-separated values), plain text and JSON formats.
When I needed to import new daily stats into my application, I clicked on a link labeled "new similar" beside the log entry of my initial import operation and pasted in my updated data as before, and Dabble DB performed the import without a hitch.
eWEEK Labs Executive Editor Jason Brooks can be reached at firstname.lastname@example.org.