Feeless Transactions Called Into Question: Hive As A Social Media Network

We often discuss that fast and feeless transactions are one of the things that separates Hive from other blockchains. The fact that we utilize the resource credit system as compared to direct transaction fees is a game changer.

As noted in the past, interaction with the network with transaction fees is an expense. On Hive, one makes the investment because access is granted through the use of Hive Power. This is what correlates into resource credits, a non-tradeable token that quantifies each activity on-chain.

This has some of use excited about the future. Of course, there are people who call into question the viability of it. Are some of us off our rocker because we believe the long term potential? Do those people who believe that Hive cannot scale due to rising RC costs have a point.

It is what we will discuss in this article.

Social Media On Hive

The image above is the most recent gas fees on Ethereum according to gasprice.io. As we can see, paying over a dollar for each social media activity is a non-starter. In fact, I maintain that even half a cent on other networks makes it impossible long term.

Simply put, people are not going to pay tx fees each time they upvote or comment.

That said, social media networks do have costs. This is true whether we are discussing Hive or Facebook. Hardware costs money and servers are not free. For this reason, we have to attribute the costs in some manner.

We all are aware of how traditional social media operates. What we often do not think about is how powerful their model is. The network effect is what pushes the value up exponentially. However, since their cost are computer-related, those tend to decrease over time.

Here is the golden nugget. Storage (and processing) get less expensive with each new generation. At the same time, we see performance increase. Basically, this is a more for less model.

This is one piece of the pie for Hive.

Cost Per Transaction

At this moment, there is a cost to the system. For our example we will use $1M. This is a nice round number. We will also start with 100K transactions.

The presumption is that RC cost for each activity has to go up. Is this reflected in the numbers?

With our example, if the cost is $1M and we have 100K transactions, obviously we are looking at $10 apiece. In other words, the cost/tx is $10.

What if the volume jumps to 1M? Under this scenario, the cost is $1. Here we see how the number of transactions went up yet the cost for each decreased.

It is a fact that is often overlooked.

Naturally, this is only possible when excess capacity resides within the system. As long as the present hardware can process the 1 million transactions, there is no problem. If, however, the mast is 250K, then something has to give.

Under this scenario, we have to either upgrade the network, experiencing further cost increases or see a backlog transactions, causing prices to go up as we often see with Bitcoin and Ethereum.

So what is the solution?

Scaling The Network

Hardware advancement is not the only area. We see progress being made with compression, data architecture and software design. All of this factors in.

Since Hive came into existence, one of the main areas of focus is scaling of the network. This not only applies to total transactions that can be processed. It also applies to the cost of running the operations.

In the last hard fork, we saw a reduction in the size of the blockchain data. It was almost halved in what it was before. Here is where we see a drop in the cost for storage. If the size goes from 750GB to 400 GB, this can be housed on a smaller server.

This equates to less cost.

We also saw a redesign in how the data is shared. Now, the block producers compresses the data before sending it to the other nodes. This removes the necessity for each node to compress every block, an obvious waste of resources.

Here we have an ongoing quest. Scaling never stops either in technological advancement or programming on Hive. It all ties to efficiency. We know that, based upon the past 40 years, the hardware we will be dealing with in 3-5 years will be more advanced than today. It will also likely be cheaper, at least form a cost/performance standpoint.

Resource Credits

Resources Credits are designed to capture these costs and quantify them on a transaction basis. There is no doubt that as more transactions occur, the cost of running the network increases. In raw numbers, this is unavoidable.

That said, there is no guarantee the costs go up at a rate faster than the growth capabilities of the network. In fact, the sustainability of these types of systems relies upon it. After all, this is the wave that Google and Facebook rode.

Recourse Credits basically allocate the cost of the network to each activity based upon the resources used. This is why account creation is more expensive than a comment. For the former, more network resources are used.

Again, this is only for on-chain activity. There is a reason why we are looking at the development of sidechains, especially when it comes to smart contracts and Hive Application Framework (HAF). The idea is to keep the base layer tight in terms of functionality.

Even Vitalik Buterin echoed similar sentiments about Ethereum recently. He noted that expanding the core functionality of the network would come at a cost and a minimalist approach was better.

This is the approach Hive always took.

Resource Credits are tied to cost. They are set by the witnesses based upon the allocation of resources along with the overall operations. For years, the trend was for rising costs as the database grew. This was reversed over the last couple years as focus started to pay out. Even though it is larger, the cost of the total chain is less expensive today than it was 3 years ago.

Reason For Optimism

Why should we believe this will continue?

The answer lies in the fact that everyone is in the same boat. It doesn't matter whether it is Hive, Facebook, or Goldman Sachs. All entities are facing the problem of every increasing data. It is growing exponentially with no signs of slowing down.

This means that the entire industry is going to be focusing upon different packet architecture, laying optimization, and sharding techniques. Data distribution and storage will also be altered. Maybe the database is broken down and a subset node system is created. Instead of every node having the entire blockchain, it is divided among groups of Witness nodes, with each housing a portion of the database.

People consistently underestimate the scaling potential of the industry. Data is something that gets a lot of attention. Hive is not the only network with this problem. That means solutions will come about that Hive can incorporate that affect the total cost of operation.

In the end, that means we could see RC pricing staying the same or potentially even going down. If the scalability of the network increases yet costs remain fairly constant, then we can how this works out on a per transaction basis.

Not only is there internal measures that are being taken, we have an entire industry focused upon being able to house and process more data for less money.

This is what is going to allow Hive to keep operating as a social media network.

After all, scaling does not mean handling more transactions at any cost. It means doing so in a cost efficient manner.

In the end, the progress made there is reflected in the costs of RC.

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