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Tables Are Dead: How to Overcome Relational Model Limitations





  Table of Contents:
  1. Tables Are Dead: How to Overcome Relational Model Limitations
  2. Limitations of Row-and-Column Database Systems
  3. Improvements to Row-and-Column Database Systems

The classical relational model has been the universal row-and-column structure for storing and processing data for decades. But with data volumes nearly doubling each year, the relational model is no longer adequate. Tables are not designed for analytics and data stored in tables is not inherently searchable. Here, Knowledge Center contributor Charles H. Silver explains how to remove the scalability problems associated with antiquated data management systems that are based on the classical relational model.

Tables Are Dead: How to Overcome Relational Model Limitations - Improvements to Row-and-Column Database Systems
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Improvements to row-and-column database systems

These problems are certainly not entirely unknown. When employees spend their working lives managing tables, it's not likely that they never thought, "There must be a better way to do this." As technology and business executives spend millions on servers, software and services, you can bet they looked for a more cost-effective way to get what they need.

In fact, a slew of vendors have emerged to solve these problems with incremental improvements on row-and-column database systems. These include proprietary hardware and massively parallel clusters of computers working with column-oriented systems.

Many of these demonstrate significant performance improvements but are still limited by the rigidity of the classical relational model. Table upkeep, manual performance tuning, indexing and loading processes remain. Additionally, the expense in hardware, custom programming and software licenses means organizations are emptying their pockets for the analytics performance they direly need.

Remove constraints imposed by classical relational model

To break free from the shackles of rigid static rows and columns that are holding us back, we need to toss the incremental improvements on the classical relational model to the wayside and create new models. Once data is no longer constrained by rigid, static row-and-column structures, computers can automatically restructure data to dynamically optimize performance and adjust to new queries with mathematical precision.

Additionally, by removing the constraints imposed by rigid, static data structures and enabling computer software to manipulate data in any structure, we can better analyze unstructured data and remove the scalability problems associated with antiquated data management systems based on the classical relational model.

To upgrade databases from a wagon to a jetpack, we need to remove ourselves entirely from the constraints imposed by the classical relational model and create a better way.

Charles H. Silver is CEO at Algebraix Data Corporation. Charles has more than 25 years of experience as a successful entrepreneur. Most recently, he sold new media company RealAge Inc. to Hearst Corporation in 2007. Charles founded RealAge in the late 1990s based on a ground-breaking business plan for building revenue and attracting customers. Prior to his nine years at RealAge, Charles built a series of profitable franchises in the retail and real estate markets. After graduating from the University of Michigan in 1981, Charles spent the first few years of his career as a staffer for the governor of Michigan and for a U.S. Congressman. He can be reached at CSilver@algebraixdata.com.



 
 
>>> More Database Articles          >>> More By Charles H. Silver
 

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