Directed Acyclic Graphs — a Blockchain frenemy?

A somewhat new trend of solving cases which were considered to be intractable is now making the rounds.

The general public, as well as the tech-savvy population, is searching for keywords like Bitcoin, Blockchain, crypto, and Distributed Ledger Technology to solve the cases mentioned above with the help of cryptographic principles and distributed computing.

If one were to refer to a tech business, one would know which specific term to use — social network, an online marketplace and productivity app are all different and have different functions.

However, this isn’t the case with crypto as the public generalizes all of it under ‘blockchain technology.’

This phenomenon doesn’t do justice to the otherwise complicated and widespread industry. For anyone who wants to get into this domain, it’s important to understand that in the next few years, it won’t be called blockchain.

The crypto technology is rapidly progressing and branching out into various other domains, and they’re all very different.

Currently, high throughput and vs. high precision platforms separate the industry — Bitcoin and Monero are the most accurate examples of high precision protocols.

The name is drawn from the system’s ability to enable users to make secure, reliable and somewhat anonymous transactions. It is impossible to fake a sale or to manipulate the system — sizeable financial trading, voting system make use of this system where double reliability is essential.

Although secure, there are a few limitations to the network as mentioned above — not useful for other operations. To tackle this, we have “high throughput.” Tasks that are inclusive of a more significant number of data transfer — either concerning data volume which is calculated in GB per day or data frequency.

If these platforms — Internet of things and collaborative research are run on the Bitcoin blockchain, it would be unnecessary because these business cases involve very regular database updates on the blockchain

If you have heard of Directed Acyclic Graphs, it’s because many prospects are using high-throughout category and DAGs is grabbing all the eyeballs.

For platforms that require high throughput, DAGs are a game changer.

Some of the most popular ventures churned out using tangle are the ones in connect with IoT. In this close competition stand IOTA and IoT Chain.

They are both propellers and are leading the research state towards DAG information.

Another venture that comes in the picture is something called the ‘CyberVein’ that boasts of a more progressed capacity by making use of a more inclined and more well-organized consensus procedure called the Proof of Contribution (PoC) to facilitate bigger datasets on the DAG a reality.

Another one in the race is the ByteBall, which reportedly speeds up crypto payments globally. Well, there are not the only market leaders in the DAG domain, newer ones are always waiting for the opportunity to test waters of the DAG concept.

How the DAG came to be

To fully understand what DAGs are all about, it is essential to declutter the term into its parts. The graph speaks of a web of nodes and edges (the connection between nodes) that have particular features. To put it into perspective, a relationship chart of your friends and family can be portrayed with the help of edges that are complex and bidirectional as different individuals can have complicated relations with one another.

This ‘Acyclic’ term goes back to the characteristic of connections transactions, concerning cryptocurrency) and how they cannot find their way back to the original node, no matter how hard they try. One could call it a tree of nodes instead of a loop of nodes.

Now, looking into its ‘direction’ — the edges or connections between the nodes are only one directional.

An important learning that one can take away from this configuration is the efficiency of this system that ensures manipulation of the census is kept at bay, owing to built-in checks on the network.

This also promises that each node will be allotted a full copy of the ledger, at all times so that different segments of the system can operate individually, on a larger scale than the blockchain network. However, the record of trade is a domain that is nearly impossible to deceive.

Use cases

While there may not be enough clarity on the dissimilarities among several crypto platforms and they may appear involved. However, they will have an underlying effect on the types of use cases suitable for every platform. There exist some clear-cut characteristics that stand out following the need for DAGs, as established earlier.

Firstly, the essentials put forth on the blockchain by the IoT systems comprising of thousands of data points connected to sensors in cars, offices, homes, and everywhere else would exhaust the blockchain based structure.

Secondly, some use cases make use of in-depth combinations like scientific research, that will prove to be very invasive for a blockchain structure. And lastly, there arises the question of massive data sets; fees per MB transmitted on the likes of the Bitcoin blockchain would sky-rocket to the level of preventing the standard of data transfer as one sees in regular business applications, keeping aside the enormous amounts required for Big Data.

The crypto community splits ways?

The cryptocurrency domain has witnessed more than just a few controversial debates over the years, but this comes as a disappoint to the drama-hungry public. There apparently will be no bad blood between of the crypto community between DAGs and the Blockchain. They are two different platforms that cater to two different needs, as mentioned above. This positive relationship between the two paves the way for high throughput and high accuracy platforms to communicate dynamically.

Directed Acyclic Graphs — a Blockchain frenemy? was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.