Aptos VS Algorand: Which One is Better?
Published on June 7th, 2023
If you've been delving into the exciting world of cryptocurrencies and blockchain technology, you might have come across these two names, sparking curiosity about their unique features and advantages.
Today, we embark on a journey to explore the similarities, differences, and distinctive characteristics of Aptos and Algorand, allowing you to make an informed decision in this ever-evolving crypto landscape.
By examining their core features and consensus protocols, we will uncover the secrets that set them apart. So, prepare yourself for an enlightening journey as we uncover the details that will shed light on the ultimate question: which one reigns supreme in the realm of cryptocurrencies, Aptos or Algorand?
When comparing Aptos and Algorand, Aptos emerges as the superior network. Aptos demonstrates higher transaction throughput (160k TPS compared to Algorand's 6k TPS, faster transaction finality (500 milliseconds on Aptos compared to 5 seconds on Algorand), and a more advanced consensus algorithm. Aptos also has a larger number of active developers (64 compared to Algorand's 26), indicating a robust ecosystem. Furthermore, Aptos has a slightly higher number of validators, making it slightly more decentralized. However, Algorand has a lower capital requirement to run a validator (1 ALGO compared to 1,000,000 APT for Aptos), providing more accessibility and inclusivity.
In this passage we compare Aptos and Algorand with a variety of perspectives, such as technological capabilities, tokenomics, current value metrics, decentralization and more!
Let’s get started.
Before we begin, we need to make sure that we understand Aptos and Algorand.
Aptos, a recently launched blockchain platform in October 2022, seeks to tackle the scalability and energy consumption concerns associated with other blockchain platforms.
One noteworthy aspect of Aptos is its utilization of the Move programming language, developed by the Diem blockchain team at Facebook. Move is designed to provide a secure and reliable language for crafting smart contracts, featuring automated resource management and a linear type of system.
Additionally, Aptos employs its own block-STM data structure, which is optimized to enhance the speed of block propagation and storage efficiency.
The block-STM serves as an execution engine for transactions on the Aptos blockchain platform, prioritizing faster block propagation and efficient storage. It aims to enhance the overall performance and scalability of the blockchain, making it a more practical and efficient solution for various use cases.
In essence, Aptos aims to present a more efficient and sustainable alternative to other blockchain platforms, positioning itself as an ideal choice for decentralized finance (DeFi) and non-fungible tokens (NFTs) applications.
While it is still relatively new and awaits widespread adoption, the platform's unique features and innovative approach make it a captivating contender in the ever-evolving realm of blockchain technology.
Algorand is a prominent blockchain and cryptocurrency platform founded by Silvio Micali, a renowned computer scientist and Turing Award winner. It was established with the aim of addressing some of the key challenges faced by traditional blockchain networks, such as scalability, security, and decentralization.
Algorand utilizes a unique consensus protocol known as Pure Proof-of-Stake (PPoS), which enables fast and secure transaction processing while ensuring decentralization.
The PPoS consensus protocol employed by Algorand is designed to achieve consensus in a highly decentralized manner. It allows users to participate in the consensus process and propose new blocks based on the amount of Algo tokens they hold. This approach eliminates the need for resource-intensive mining and ensures a fair and efficient system.
Algorand has formed notable partnerships with various organizations and institutions across different sectors. For instance, it has collaborated with the Marshall Islands to develop the world's first national digital currency, known as the Marshallese sovereign (SOV).
Additionally, Algorand has partnered with World Chess to create a blockchain-based platform for organizing and managing chess tournaments. These partnerships demonstrate the versatility and potential of Algorand's blockchain technology in diverse domains.
When it comes to comparing blockchain networks such as Aptos and Algorand, we need to compare them via metrics that matter. Transaction fees, throughput, and finality are just a few metrics that are important to people and users when it comes to using and adopting these networks.
The most sophisticated networks often rise to the top in terms of adoption and valuation. Other factors which we discuss later also influence this process. Moreover, in this passage we compare Aptos and Algorand with respect to technological features. We summarize our findings in the table below.
|Aptos VS Algorand: Technological Foundation|
|Max TPS Throughput||160,000||6,000 TPS|
|Virtual Machine||Move Virtual Machine (MVM)||Algorand Virtual Machine (AVM)|
|Main Smart Contract Language||Move - Core||Transaction Execution Approval Language (TEAL)|
|Avg. basic Transaction Fee||0.000585 APT
|Consensus Algorithm||Proof of Stake + BFTv4 + Bullshark||Pure Proof of Stake (PPoS)|
|Total Validators Online||108||93|
|Minimum Required to Run a Validator||1,000,000 APT or (About)$8,320,000||1 Algorand or about $0.16|
|Block Production Time||0.33 Seconds||3.75 Seconds|
|Transaction Confirmation Time / Finality||500 milliseconds||Under 5 Seconds|
|Modular Blockchain Architecture?||Yes||Yes|
|EVM Compatible||No||Yes, in Layer 2 Rollup Called Milkomeda A1|
Firstly, Aptos seems to be more advanced and better than Algorand in that it processes about 10x more transactions than Algorand. Aptos has a max throughput of 160k TPS whereas Algorand has a throughput of 6k TPS.
Both Aptos and Algorand have different virtual machines, Though this is because they have different smart contract languages. Aptos uses the Move smart contract language whereas Algorand uses the Transaction Execution Approval Language (TEAL).
Another big difference between Aptos and Algorand is the cost to perform transactions on the network. When it comes to transaction fees, Algorand beats Aptos, boasting a low base fee of about $0.0002. The Aptos Network, on the other hand, charges about $0.004797 per basic transaction fee.
Thirdly, one main difference between Aptos and Algorand is the sophistication in their respective consensus algorithms. The Aptos consensus algorithm is composed of 3 sections, Proof of Stake, Bullshark and AptosBFTv4. For Algorand, it is a more refined version of PoS, PPoS or Pure Proof of Stake.
A more sophisticated Consensus algorithm contributes to the incredible throughput that Aptos is able to handle.
Aptos also seems to have more validators online. Though, Validators on Algorand require much less capital to participate in their consensus. Validators on Algorand also go by the term “Proposers”. One negative feature of Algorand is that proposers don’t actually get rewarded for running their nodes. In Aptos, Validators get rewarded with minted Aptos coins, as well as stakers.
Furthermore, we can see that Aptos is better than Algorand when it comes to technology by comparing them through the transaction finality metric. It takes 500 milliseconds for a TX to get confirmed on Aptos, compared to 5 seconds on Algorand. Aptos also produces blocks every 333 milliseconds, compared to Algorand which produces blocks every 3.75 seconds on average.
Several features that make Algorand more competitive than Aptos is its capability to execute Atomic swaps. With this feature 2 transactions either succeed or fail at the same time.
Algorand also has a layer 2 rollup solution that incorporates EVM compatibility. This effectively makes Algorand more interoperable with other blockchain networks such as Ethereum, BSC, Polygon, OP, and Arbitrum.
Decentralization is the one metric that is most concerning when it comes to cryptocurrencies. The very purpose of cryptocurrencies such as Bitcoin is to be decentralized and trust-less. So, when it comes to Aptos and Algorand, which is more decentralized?
We answer this question in this passage. We compare some metrics of Aptos and Algorand to figure out which network is more decentralized.
|Decentralization: Aptos VS Algorand|
|Number of Validators||108||93|
|Capital Required to run a Validator||1,000,000 APT||1 ALGO|
|Capital Required to run a Validator(In USD)(As of June 2023)||$8,900,000||$0.16|
|Consensus Mechanism||PoS + AptosBFTv4 + Bullshark||Pure Proof of Stake (PPoS)|
What exactly do the metrics above mean? Let us explain.
In terms of the number of validators, Aptos has 108 while Algorand has 93 validators. Although Aptos has a slightly higher number, the difference is relatively small and may not be a significant factor in determining decentralization. Moreover, Aptos is still slightly more decentralized than Algorand.
When considering the capital required to run a validator, Aptos requires 1,000,000 APT tokens, whereas Algorand requires only 1 ALGO token. This indicates that Algorand has a lower entry barrier in terms of capital requirement, potentially allowing for a more inclusive and distributed validator set.
The capital required to run a validator in USD as of June 2023 further emphasizes the difference. Aptos requires a significant capital investment of $8,900,000, while Algorand requires a considerably lower amount of $0.16. This suggests that Algorand offers a more accessible opportunity for individuals to participate in the network's validation process, contributing to its decentralization.
Regarding offline time, both Aptos and Algorand exhibit no reported instances of offline time. This indicates that both networks prioritize uptime and reliability, contributing to their decentralized nature.
In terms of governance, Aptos follows an on-chain governance model that allows the community to vote on proposals and submit Aptos Improvement Proposals (AIPs). On the other hand, Algorand also adopts an on-chain governance model but has an oversight body known as the Algorand Governance Committee (AGC) that reviews and votes on Algorand Improvement Proposals (AIPs).
Both models provide avenues for community involvement and influence in the decision-making process, promoting decentralization.
Regarding the consensus mechanism, Aptos employs PoS (Proof of Stake) combined with AptosBFTv4 and Bullshark. Algorand, on the other hand, utilizes Pure Proof of Stake (PPoS). These two consensus algorithms invoke a strong form of decentralization.
Lastly, the number of active developers is higher in Aptos with 64 compared to Algorand's 26. More active developers can contribute to the ongoing development and enhancement of the network, potentially leading to a more decentralized and robust ecosystem.
Another important perspective that can be used is valuation and Adoption value.
Like other assets, Cryptocurrencies often become overvalued and undervalued. It would be beneficial to retail investors to know when these cryptocurrencies might be overvalued or undervalued. We might be able to know whether or not Aptos or Algorand are overvalued or undervalued relative to each other.
We can estimate the fundamental value of Aptos and Algorand and compare them using a variety of metrics. In the next table we illustrate these metrics.
|Fundamental Value Metrics: Aptos VS. Algorand|
|Marketcap (As of June 2023)||$1.624 Billion||$980 Million|
|Total Value locked (TVL) (As of June 2023)||$ 54 Million||$158 Million|
|TVL to Marketcap Ratio (as of June 2023) [ Higher is better]||0.0332||0.1612|
|Fully Diluted Marketcap (As of June 2023)||$8.422 Billion||$1.348 Billion|
|TVL to Fully Diluted MC ratio [Higher is better]||0.0064||0.1172|
|Total DEX Volume(7d) (As of June 2023)||$3.765 Million||$6.981 Million|
Which is more overvalued, Aptos or Algorand? Well, it appears that Aptos is more overvalued in comparison to Algorand. We can conclude this via the following metrics.
The TVL to MC ratio is higher for Algorand. This means that people are more willing to lock up their tokens in the Algorand protocol as opposed to in Aptos. We can see again that people are also using Algorand much more since it has higher DEX volume too.
For every million marketcap, people are willing to lock up more capital in Algorand than in Aptos. We can conclude that people are utilizing Algorand more than Aptos.
Algorand is both undervalued in the short term and in the long term according to the TVL to MC ratio and fully Diluted MC ratio. We can see that when it comes to fully diluted marketcap the ratio is higher for Algorand in comparison to Aptos.
Another perspective that can be used to compare cryptocurrencies to figure out which one is better is Tokenomics. Tokenomics is essentially the token economics of cryptocurrencies. This involves complicated traits such as demand, supply, inflation and much more.
The reason why tokenomics are important to consider when comparing cryptocurrencies is that Tokenomics have a great deal of influence over how well cryptocurrencies perform when it comes to price appreciation or value sustainability.
In the next portion of the passage, we compare Aptos and Algorand using the Tokenomics perspective.
|Tokenomics: Aptos VS Algorand|
|Circulating Supply (As of June 2023)||200.2 Million APT||7.25 Billion ALGO|
|Circulating Supply of Total Supply Percentage (As of 2023)||19.27%||72.49%|
|General Inflation Rate||6.99%||5.448%|
|Circulating Supply Inflation rate (2023)||41.53%||8.828%|
|Circulating Supply Inflation rate (2024)||117.93%||8.5467%|
|Circulating Supply Inflation rate (2025)||36.65%||8.29%|
|Circulating Supply Inflation rate (2026)||22.6%||8.06%|
|Points of Demand (What creates demand for the coin)||
|Burning Mechanism?||Burns All Transaction Fees||None, Though the Foundation Burn early redemption tokens|
|Burnt Tokens||Burns about 100-250 APT at current transaction rates per year||19.9 Million ALGO|
Token economics is a crucial aspect of cryptocurrencies, let’s analyze which has superior tokenomics, Aptos or Algorand.
Let’s get something straight, when it comes to digital assets, they need to have certain qualities that allow them to retain and grow their value, for them to be great assets.
The first is the general inflation rate. This inflation is a result of minting coins to reward people who stake and run validators. They are used as incentives to keep the network safe and running. We can see from the table above that Algorand has a lower inflation rate.
Because Algorand has a lower inflation rate than Aptos, it is more likely to retain its value now as opposed to Aptos.
Secondly, is the CSTSP Metric which measures the percentage of released tokens compared to total supply. An optimal CSTSP is above 70%, the higher, the better.
The reason why a higher circulating supply as a percentage of total supply is better is because as tokens get unlocked, they eventually find themselves being sold in the market. This inevitably creates sell side pressure.
Cryptocurrency foundations, or the teams behind the cryptocurrencies, often lock up tokens so that the price can increase in the short term. Investors who fund these teams also have their tokens locked up. These investors eventually sell them to take a profit on their investments.
Algorand has a higher circulating supply of total supply compared to Aptos which has a lower. This creates a much higher circulating supply inflation for Aptos than for Algorand. Algorand clearly has better tokenomics than Aptos, from this point of view. For Aptos, the circulating supply is set to increase by large percentages in the coming years.
A third metric of Tokenomics is the points of demand that the coins have from its ecosystem. Both Aptos and Algorand are required to execute transactions in their respective ecosystems. They are both used as capital in DeFi, and they are both used to earn yields by staking.
One difference is that Algorand requires ALGO coins for people to be able to participate in governance. Aptos, on the other hand, doesn’t. Another difference is that 1 Million Aptos is required for people to be able to run validator nodes.
Algorand needs 1 ALGO which is insignificant. Aptos seems to have more demand than Algorand just because running a validator is more lucrative and attractive than participating in governance.
Aside from this difference, People can participate in the Aptos and Algorand network by staking their assets. Aptos and Algorand coins are required to be able to earn this passive income. To some people, this seems like a great way to earn revenue. Since Aptos and Algorand are required to generate the revenue, people have to buy the coins on the open market, creating demand for the coins.
Lastly, Algorand has burned many more coins than Aptos, However Aptos actively burns coins. Every transaction fee on Aptos gets burnt. As Aptos gets more adoption, more coins are going to be burnt. The only negative about this is that currently, because Aptos isn’t being used, Aptos isn’t burning a lot of coins.
Algorand doesn’t have a system in place that actively burns ALGO coins.
All in all – Algorand has lower overall coin inflation than Aptos and has burnt more coins. In contrast to Algorand, Aptos has more points of demand and an active coin burning feature.
It is no surprise that Aptos and Algorand have differences. They also have similarities. We have summarized the most important differences and similarities between Aptos and Algorand and illustrated them in the infographic below.
In conclusion, when comparing Aptos and Algorand from a technological standpoint, Aptos emerges as the superior network. Aptos demonstrates higher transaction throughput, faster transaction finality, and a more advanced consensus algorithm, which contributes to its impressive capabilities.
Additionally, Aptos has a larger number of active developers, indicating a vibrant ecosystem for ongoing development and decentralization.
In terms of decentralization, both networks exhibit robust characteristics. Aptos has a slightly higher number of validators, indicating a decentralized validator set. However, Algorand surpasses Aptos in terms of a lower capital requirement to run a validator, making it more accessible and inclusive for individuals to participate in the network's validation process.
Both networks prioritize uptime and reliability, with no reported instances of offline time. Moreover, both networks employ on-chain governance models that allow community involvement, further promoting decentralization.
When considering tokenomics, Algorand outperforms Aptos in several aspects. Algorand demonstrates a lower inflation rate, making it more likely to retain its value over time. It also has a higher circulating supply as a percentage of total supply, indicating better sell-side pressure management.
Algorand's demand points from its ecosystem, including participation in governance, are significant, while Aptos mainly derives demand from running validator nodes. Furthermore, Algorand has burned more coins, contributing to lower overall coin inflation.