Using the blockchain to transform data management itproportal gpu z database

It’s truly the Information Age, and we are drowning in data. As recently as 2013, it was estimated that 90 per cent of all the data in existence had been created in the few years prior — and the pace has only picked up since then. We — and our machines — are constantly generating a tsunami of new data. Along with the sheer volume of data generated, we’ve also made great strides in the breadth of what we’re able to collect, store and analyse.

The amount of data is only going to increase with the rise of big data. With the Internet of Things (IoT), artificial intelligence (AI) and advanced analytics driving the trend for big data, it’s expected to represent 30 per cent of data stored in data centres by 2021. Current data storage challenges

Around 80 per cent of big data is unstructured, and current databases, designed in that ancient age before the internet, are not built to handle this type of data or the amount of it that needs to be stored.


Traditional databases, with SQL queries and relational database systems, were designed for structured data tied to very specific and narrowly focussed applications in limited domains. These systems are also limited in terms of how much data they can handle and its scope of use.

In the current data storage infrastructure, many companies rely on third parties for solutions such as cloud storage. This is a solution that can introduce new problems, such as the expense involved in scaling and performance issues when dealing with large amounts of data.

In addition to technical issues, traditional centralised data storage structures pose security and privacy risks — as evidenced by a growing number of high-profile data breaches. When such a breach occurs, all the contents of the database are vulnerable to attack and theft. Accommodating AI

Artificial Intelligence (AI) is a hot topic, particularly in the enterprise setting. But it’s important to remember that data is a key ingredient for training neural networks. The insights and predictions that come from machine learning algorithms can only be improved and refined by adding more data. We need more robust data storage that can handle the amount of data needed to optimise these insights. Connecting the IoT

The rise of the Internet of Things (IoT) will also require better data management structures. When interconnected devices are constantly streaming data to each other, it’s a risk to rely on a centralised server that can be prone to downtime or congestion at peak times. Making the most of data

Beyond efficiency and security, traditional data storage systems make it difficult for enterprises to realise the true value of the copious amounts of data that they are producing. Without the right systems that can produce actionable insights from this data, its value is simply left on the table. Instead of being limited by traditional databases, enterprises should be experimenting with new ways to use databases that will benefit their organisations. Enter the Blockchain

In order to meet our quickly evolving data needs, data storage needs to be efficient, resilient, highly secure and able to work with the requirements of AI and IoT applications and enhanced analytics. Blockchain technology can offer an ideal solution.

The blockchain offers a decentralised system rather than the siloed, centralised storage that currently exists. With the blockchain, distributed ledger technology allows data to be broken up and stored across a collection of nodes. In addition to this, blockchain systems are immutable, meaning that once an entry is added to a database, it cannot be removed or altered. There are many benefits to this, including:

• Security: The lack of a central point of failure means data is far more secure. Because copies of a database are synced across many different nodes, that database is extremely hard to compromise. To do so would require that a party gain control of the majority of the nodes to be able to alter the entries on the ledger.

• Sharding: The distributed nature of the blockchain can also allow sharding. Shard stands for “System for Highly Available Replicated Data,” and sharding helps partition the database along logical lines, making it easier to work with. Sharding involves distributing fragments of a file rather than sending the entire file to other nodes. This offers even more privacy and security because anyone in possession of the data will only have a small and unreadable piece of it, similar to torrenting.

• Swarming: Along with sharding, blockchain can also facilitate swarming, which divides the network up into clusters of nodes based on their geographical location. Nodes in a swarm can pull data from those closest to them, reducing latency, or download shards in parallel from multiple sources for quick retrieval. This allows the network to be able to handle high throughput around the clock.

• Incentives: Using the blockchain can also allow an incentive element, as tokens can be used to encourage peers to replicate and store files. This way, an Airbnb-like marketplace for data storage and management can be developed, using a crypto-economic network of peers.

The amount of data that individuals and organisations are producing and storing is growing exponentially as developing technology makes this data ever more usable and valuable. Blockchain technology makes it possible for organisations to work with much larger amounts of data without the computational and resource limits of traditional database systems. As the importance of data and its infrastructure continues to grow, the blockchain offers a way to move beyond the limitations of archaic data storage and into the future.

banner