Why software engineers and developers should care about blockchain technology Applications beyond digital currency Dr. Sam Siewert Email: siewerts@erau.edu Social profile: http://faculty.erau.edu/Samuel.Siewert, https://www.colorado.edu/ecee/sam-siewert Job title: Assistant Professor–Software Engineering Embry-Riddle Aeronautical University, Prescott; Assistant Professor Adjunct–Computer Engineering, University of Colorado Boulder Abstract Blockchain is a revolution for data management that you can use instead of or in addition to a traditional structured relational database management system (RDBMS). Here, you dig into R-DBMS and blockchain (beyond use for crypto-currency and Bitcoin) by using a simple JavaScript blockchain prototype that you can expand to use Hyperledger to explore an emergent use for general aviation and small unmanned aerial systems tracking. IBM has helped to bring blockchain into much wider use for everything from supply chain logistics to medical information management (IBM blockchain). At Embry Riddle, I’m working on just such a database and comparing options including R-DBMS only, blockchain only, and a hybrid solution. I’m still working on determination of what will be best, but the more I learn about blockchain, the more interested I have become. While we have yet to settle upon a data management solution, we know we need to replace our flat files as our system grows, and we’re most likely going to use a combined approach with both R-DBMS and blockchain distributed applications. A Brief History of Data Management and Processing Relational database management systems (R-DBMSs) evolved as a formal method of manipulating data independent of data processing, the goal being to create a language (which became the Structured Query Language [SQL]) for querying (that is, to relate data in tables with primary and foreign keys, as shown in the Figure 4 schema for our working example) and to insert, update, and delete records in one or more tables consistently. IBM engineer E.F. Codd formalized relational algebra to reference data in related tables, which became core SQL. At the time, data integrity was a primary concern in addition to the ability to produce informational reports that combined data from normalized tables to support business decision making while avoiding loss of integrity caused by data hazards.