Suppose I brought into work an Apple II computer from 1977. This one-time state-of-the-art machine sports a 1MHz processor, 4KB of RAM and a monochrome video controller. It comes from the same era as the Atari, the Commodore 64 and the TRS-80. Obviously, these computers (as well as their operating systems, floppy drives, keyboards and displays) are now nostalgic antiques, not business computers.
But before the first microprocessor emerged, which made affordable home computers such as the Apple II possible, Edgar Frank Codd introduced a breakthrough in his landmark paper, "A Relational Model of Data for Large Shared Data Banks," which would mark the invention of the rows-and-columns database dubbed "the classical relational model."
The classical relational model, which predates the commercialization of the Internet, is today a crucial element in the mission-critical systems of nearly every Global 2000 company. But consider three important things that have transpired during the lifetime of this rows-and-columns paradigm:
1. The largest databases in the world have gone from virtually nothing to 100 terabytes to multiple petabytes.
2. Throughout the 1980s and 1990s, structured data dominated databases. But today, unstructured data is growing at nearly double the pace of structured data. Additionally, the way we use data is increasingly focused on analytics.
3. Computerized analytics, which did not exist at the time the rows-and-columns database was invented, has become a market of over $20 billion.
Despite the challenges the classical relational model imposes on scalability, performance and manageability in the face of modern data volumes and applications, it continues to stick as the status quo. The rest of the technology ecosystem has developed at a torrid pace, but the rows-and-columns paradigm remains virtually unchanged after decades. It's like using millions of floppy drives in an age of streaming high-definition movies or playing pong in an era of supercomputers.