Monad is a layer-1 scaling solution that promises extreme scalability, near-instant transactions, and full EVM compatibility — features that offer practical solutions to persistent blockchain bottlenecks. In this quick guide, we discuss how Monad works, its use cases, key benefits, and the challenges facing the network.
In this Guide:
- What is Monad?
- How Monad works
- MonadBFT consensus
- Monad use cases
- Monad vs. alternatives
- Possible risks
- Is Monad the next big thing?
- Frequently asked questions
What is Monad?
Monad is a powerful, EVM-compatible layer-1 (L1) blockchain that can achieve a throughput of up to 10,000 TPS with a block time of one second. It was first launched in 2022 by Monad Labs, led by co-founders Keone Hon (CEO), James Hunsaker (CTO), and Eunice Giarta (COO). The testnet officially went live on Feb. 19, 2025.
Monad addresses the core scalability limitations common to EVM-compatible blockchains. Ethereum, for instance, handles only around 15–30 transactions per second (TPS). This limitation can — and does — cause significant delays and congestion during peak usage.
Monad resolves such bottlenecks by enabling dramatically higher throughput and significantly reducing congestion during periods of increased demand. Its parallel architecture supports substantially higher performance without compromising compatibility.
How Monad works
Monad significantly enhances Ethereum Virtual Machine (EVM) performance without sacrificing compatibility. It accomplishes this by implementing advanced technological mechanisms designed for higher efficiency and scalability.
More specifically, it introduces four core optimizations: parallel execution, deferred execution, MonadBFT consensus, and MonadDb.
Parallel execution
Traditional EVM-compatible blockchains, like Ethereum, Avalanche, and BNB Chain, process transactions sequentially. Monad, in contrast, executes transactions in parallel, which then paves the way for greater throughput.
Here’s how it goes — blockchains first verify transaction dependencies before allowing parallel execution. Monad, on the other hand, uses optimistic execution, with the presumption that transactions are independent. It then executes them simultaneously.
If two interdependent transactions conflict during parallel execution, Monad dynamically identifies the issue. The system then rolls back the conflicting transactions and re-executes them sequentially without compromising the overall throughput.
Deferred execution
Monad separates transaction execution from the consensus process. Traditional blockchains require transactions to fully execute before nodes can reach consensus on transaction ordering, which can slow down overall processing.
In contrast, Monad nodes first achieve consensus on transaction order before executing the transactions themselves. This “deferred execution” means nodes agree on a block’s transaction order independently from executing those transactions. As a result, transaction execution no longer delays the consensus process.
This design increases network throughput and overall efficiency.
MonadBFT consensus
Monad also uses MonadBFT, a highly optimized consensus mechanism derived from the HotStuff Byzantine Fault Tolerance (BFT) protocol. MonadBFT streamlines consensus by reducing HotStuff’s three-phase confirmation process down to just two phases. This significantly expedites block finalization.
MonadBFT operates by having the leader node propose a block and prove the validity of the preceding block. Validators then send direct confirmations to the next leader node to approve the block. This approach eventually speeds up consensus compared to more traditional methods.
MonadDb
MonadDb is Monad’s custom-built state storage database, designed specifically to support parallel transaction execution and optimized state storage. Traditional Ethereum-compatible blockchains typically embed different data structures into Ethereum’s Merkle Patricia Trie. This archaic approach can create inefficiencies due to incompatible or suboptimal integrations.
Since Monad executes transactions parallelly, its database must efficiently handle simultaneous reads and writes. MonadDb solves this by implementing a “custom” Patricia Trie structure optimized for parallelism.
This way, MonadDb delivers quick transaction processing with reduced latency by focusing primarily on current state data instead of historical data.
This efficient data structure allows MonadDb to achieve superior database performance while significantly outperforming Ethereum’s standard implementation in terms of speed and responsiveness during high-throughput scenarios.
Monad use cases
With its superior throughput and higher scalability, Monad shows great potential in several domains, including but not limited to:
DeFi applications
Monad’s ability to support the simultaneous processing of thousands of transactions allows decentralized exchanges to handle real-time order books similar to centralized exchanges.
Similarly, MonadBFT’s rapid one-second finality provides timely price updates, which makes on-chain high-frequency trading practical. Complex operations, like flash loans or multi-step arbitrage, can execute atomically and efficiently.
Gaming and NFTs
Complex gaming ecosystems, which include trading items or transferring assets, benefit from Monad’s minimal latency and extremely low fees.
NFT marketplaces can efficiently manage bulk minting or simultaneous transactions, which makes the network suitable for high-volume, low-cost NFT use cases.
Enterprise and IoT
Monad’s parallel processing makes it ideal for enterprise and IoT applications demanding high-frequency, simultaneous data handling. Enterprises dealing in IoT or industrial applications can verify and log multiple data streams concurrently to ensure accurate, timely state confirmations.
Similarly, industrial monitoring platforms, supply chain tracking, and sensor data verification are much more practical with Monad’s low-latency, parallel execution capabilities.
Monad vs. alternatives
Possible risks
Despite all the benefits, Monad’s innovations do, in fact, increase technical complexity to a notable extent. This complexity could potentially raise development and maintenance costs — more so for smaller teams.
Additionally, advanced mechanisms like parallel execution might introduce unforeseen vulnerabilities.
This token distribution model allows a small number of stakeholders to exert significant influence over critical protocol decisions. This could potentially undermine decentralization and the network’s long-term security.
Is Monad the next big thing?
Well, it’s still a bit early to say definitively. However, Monad’s technical innovations clearly position it as a strong contender among next-generation blockchain solutions. If its ambitious goals of scalability, EVM compatibility, and user-friendly development are fully realized, Monad could significantly reshape blockchain adoption (for the better). For now, it is a promising platform worth watching closely.
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