DLT vs Traditional Databases

In the constantly changing world of data management, it is essential to recognize the differences between Distributed Ledger Technology (DLT) and conventional databases. Exploring these distinctions with a focus on business and project management can help uncover their true value propositions.

Problems with Traditional Databases:

Legacy Mainframes:

Many companies still need old mainframes, coded in outdated languages, with complex and often poorly designed architectures. These systems are challenging to maintain, upgrade, and replace.

Data Architecture Complexity:

Beyond the database itself, other data architecture components play a vital role. Poorly designed non-database components can lead to data infrastructure issues.

Refactoring Limitations:

New data architectures are sometimes refactored into older programming languages, missing out on the full benefits. A complete upgrade of the data model and software codebase is essential for optimal results.

Data Infrastructure Layers:

Digital infrastructure comprises layers of software stacked upon each other. Each layer builds on lower layers, adding functionality. However, poor design in non-database components can cause issues.

Traditional Databases: Ideal for small use cases where trust and robustness are not critical. They are quicker and cheaper to use.

DLT: Eliminates the need for centralized databases, relying on a decentralized ledger. It offers high security by avoiding a single point of breach.

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Why DLT Matters:

Security: DLT’s decentralized nature ensures robust security. Breaching data in a DLT-powered network requires compromising multiple computers within the network.

Transparency: DLT offers an unchangeable and secure record, improving transparency and confidence.

Moving past Cryptocurrencies: While blockchain initiated the trend, DLT reaches further than just cryptocurrencies, with uses in supply chains, healthcare, and other industries.

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Shree Tripada Infomedia India Private Limited

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