The Monad Tech Stack Explained

Let’s talk about performance and scalability in the world of EVM (Ethereum Virtual Machine) blockchains. The EVM powers most decentralized applications (dApps) and smart contracts you see on Ethereum and many other networks. Yet, you’ve probably heard people complaining about network congestion, slow speeds, or high fees. That’s because current EVM-based blockchains (including Ethereum itself and many Layer 2 solutions) don’t always prioritize extreme performance. This is where Monad steps in.

Monad wants to push the EVM to a whole new level—aiming for 10,000 transactions per second (TPS), 1-second finality, and full EVM compatibility. These are big promises, but Monad has built a new Layer 1 blockchain from scratch to make it happen. Instead of relying on centralized “sequencers” (like many rollups do) or making everyone buy super-expensive hardware, Monad is laser-focused on innovating the entire technology stack to unlock parallel execution and faster consensus.

In simple words, Monad is creating a supercharged environment for the EVM that works on commodity hardware (like any decent PC) without sacrificing decentralization. Let’s explore how they do this step by step.

Key Insights

1. MonadBFT (Consensus Innovation): A custom consensus mechanism inspired by the HotStuff protocol, optimized for speed and efficiency.
2. Asynchronous Execution: Consensus and transaction execution happen separately (but in a sort of pipeline), allowing each to use the full block time.
3. Parallel Execution: Transactions that don’t conflict can run simultaneously, which dramatically increases throughput.
4. MonadDB (State Storage): A custom database that supports parallel access to blockchain state, removing bottlenecks when many transactions execute at once.

Put together, these innovations address crucial bottlenecks of the traditional EVM stack. If you’re new to blockchain technology, don’t worry—let’s break it all down in simple terms.

EVM and Why It Needs Acceleration

A Quick Background on the EVM

The Ethereum Virtual Machine is like a world computer that processes and validates smart contracts. Imagine you have thousands of different dApps (DeFi, NFTs, on-chain games, social networks) all running on a single global system. That’s essentially Ethereum. It’s amazing for composability (apps talking to each other) and security, but it can also get congested.

Traditional EVM-based chains (like Ethereum mainnet or certain L2s) process transactions mostly one by one in a linear sequence, which keeps everything straightforward but isn’t the most efficient way to use modern multi-core computer processors. On top of that, their consensus mechanisms often block out a good portion of each block’s time to verify transactions, leaving less time for actual transaction execution.

Enter Monad

Monad is saying: Let’s keep EVM compatibility, so all your favorite tools and applications can migrate easily, but let’s completely rethink how consensus and execution happen under the hood. The goal is to squeeze out the maximum performance from each node—while keeping the network secure and decentralized.

1. MonadBFT (A Speedy Consensus)

Consensus is how a blockchain’s nodes agree on the order of transactions. Ethereum uses a system called Gasper (a hybrid of Proof of Stake plus finality checkpoints), while many rollups basically rely on Ethereum itself for ordering (which can be slow and reliant on a single sequencer). Monad says, “We’ll build our own BFT (Byzantine Fault Tolerant) system,” which they call MonadBFT, based on the popular HotStuff protocol.

Here’s why MonadBFT matters:

• Single-Slot Finality with 1-Second Block Time Traditional BFT protocols often take three phases (or rounds) of communication among validators to finalize a block. MonadBFT cuts that down to two phases, achieving single-slot finality. That means once the network proposes a block, it can be finalized in just one second.
• Optimized Network Messages BFT systems can get chatty—validators exchange messages to confirm everyone’s on the same page. MonadBFT uses an improved message exchange process to reduce overhead. Fewer messages = faster decisions.
• Secure & Decentralized Even though it’s fast, MonadBFT is still decentralized. Many nodes participate in the consensus, keeping the chain censorship-resistant and removing any single point of failure.

Why It Helps Performance: A faster consensus method means nodes spend less time talking and more time doing. Instead of waiting around to confirm transactions, Monad quickly orders them, so the chain can move on to the actual execution part.

2. Asynchronous Execution (Separating Consensus from Execution)

Usually, on a blockchain like Ethereum or an L2, consensus and execution happen within the same short time frame per block. This leaves only a fraction of block time for execution because you also need time for consensus. That’s called interleaved execution. It’s like trying to paint your house while you’re also negotiating the cost of the paint with the store in the same small window of time.

Monad’s approach is to separate these two big tasks:

1. Consensus: The network agrees on which transactions go into the block (and in what order).
2. Execution: Nodes actually execute those transactions to update the blockchain state.

By splitting them up, Monad effectively creates a pipeline:

• While Block #N is being executed, Block #N+1 is going through consensus.
• By the time execution for Block #N is done, Block #N+1 is already settled in terms of ordering, so the node can start executing it right away.

Because of this pipeline, there’s no “rushed” timeslot for execution. The chain can constantly be executing transactions of the previous block while finalizing the next block’s order. This leads to better efficiency and higher throughput.

Why It Matters: You’re not forced to cram execution into a tiny window. Over time, this asynchronous setup results in more transactions per second and lower wait times.

3. Parallel Execution (Like Multiple Cores in Your Laptop)

Now, let’s get into what really boosts throughput: parallel execution. On most EVM-based blockchains, transactions are run one by one in a single thread. Imagine having a multi-core computer but only ever using one core to process tasks—that’s how Ethereum and many L2s handle transactions.

Monad takes a page from modern operating systems. If your laptop can run multiple programs at once (web browser, text editor, music player), why can’t a blockchain process multiple non-conflicting transactions at the same time? Turns out, it can—it’s just that we needed the right approach to do it safely.

1. Identify Independent Transactions: If two transactions touch different parts of the blockchain state (for example, one is a swap on an exchange contract, another is minting NFTs on a separate contract), they can run in parallel without interfering with each other.
2. Detect Conflicts: If two transactions do touch the same part of the blockchain state, Monad’s system marks them as potentially conflicting. They get re-checked sequentially to ensure correctness.
3. Optimistic Parallel Execution: Monad assumes most transactions won’t conflict. So it runs everything in parallel until it hits a conflict, at which point it reschedules the conflicting transaction for sequential execution to keep things accurate.

Why It’s Crucial: Modern CPUs have multiple cores. By running multiple independent transactions at once, you can drastically ramp up the number of transactions you can process in the same amount of time.

4. MonadDB (Parallel-Friendly Storage)

Parallel execution only solves part of the problem. If every transaction tries to read and write to the same database in a single-threaded manner, you’ll get a bottleneck. Monad created a custom database—MonadDB—optimized for parallel access.

Traditional EVM implementations generally use a Merkle Patricia Trie (MPT) as their data structure for storing the blockchain state. While this is secure and proven, it can become a real choke point under high parallel loads because many MPT implementations are single-threaded.

MonadDB is built with parallel reads and writes in mind. It:

• Stores and retrieves MPT data in a way that can handle many simultaneous requests.
• Uses in-memory caching and asynchronous I/O (input/output), so transactions are not constantly waiting for each other to finish reading or writing from the disk.
• Batches state updates, which is more efficient than updating everything one small write at a time.

Why This Is a Game-Changer: Even if your execution engine can run things in parallel, you still need the underlying database to be similarly efficient. Otherwise, you’re stuck waiting for a slow disk read/write. MonadDB aims to remove that bottleneck, which helps achieve that 10,000 TPS target.

Rollups vs. L1 Chains

You might be wondering, “Why isn’t Monad just doing this as a rollup?” Rollups, like Arbitrum or Optimism, rely on Ethereum for data availability (DA) and settle their transactions back on Ethereum. This can be great for certain use cases, but it also leads to:

• Centralized Sequencers: Most rollups still use a single operator to order transactions, at least for now. That’s a single point of failure or censorship.
• Extra Costs: Pushing transaction data back to Ethereum can be expensive and also limited by Ethereum’s block space.
• Slower Finality: Ethereum can take around 15 minutes for finality (depending on its consensus checkpoints). During that time, a “soft” finality from the rollup’s sequencer might not be truly final.

Monad wants to keep block production decentralized and avoid the overhead of posting transaction data to Ethereum. Their approach might not be a “rollup,” but it’s a new L1 that keeps the EVM and runs it in a more efficient setting.

Why Not Just Improve Ethereum?

Ethereum is huge and must prioritize gradual changes for stability. Implementing something like “full parallel execution” is a massive engineering and governance challenge. L2 solutions help, but many are still in “training wheels” stages, focusing on features like fraud proofs or validity proofs before tackling decentralized block production.

Monad’s solution is to start fresh with an entirely new chain and incorporate parallel execution, asynchronous execution, and a custom DB from the ground up.

Use Cases For Projects Build On Monad

1. DeFi Protocols: In high-traffic DeFi scenarios, you have thousands of trades happening at once. In a parallel environment, each trade that doesn’t directly affect the same liquidity pool or order book can run side-by-side. That means more trades can be processed per second, reducing congestion and fees.
2. NFT Minting Events: Traditional blockchains struggle during big mint events because everyone rushes in. On Monad, if each mint call touches a different token ID range or contract, many of these transactions can finalize in parallel, so you won’t get as many spikes in gas fees or failed transactions.
3. Gaming: A blockchain-based game might have players performing in-game actions simultaneously. With parallel execution, many of these state updates can happen at the same time without bogging down the entire network.
4. DApp Developers: If you’re a developer, you can still write smart contracts in Solidity, just like on Ethereum. Then, you deploy on Monad. Because Monad remains EVM-compatible, your usual developer workflow (using tools like Hardhat or Truffle) should mostly work out of the box. However, you could gain the benefits of faster finality and parallel transaction throughput for your application’s users.

External Resources For Monad

• Monad Official Website: https://monad.xyz/ Great place to learn more about the project and get official updates.
• Monad vs. Rollups Blog Post: https://monad.xyz/blog/monad-vs-rollups Delves deeper into why Monad chose to be a standalone L1 rather than a rollup.

Practical Tips for Getting Started on Monad

1. Check Hardware Requirements: Despite the high performance, Monad’s stated goal is that you can run a node on commodity hardware. Make sure to review the recommended specs on Monad’s website to see what’s required.
2. Stay Updated: Because it’s a new chain, keep an eye on announcements for any network upgrades or changes to their execution environment.
3. Deploy & Experiment: If you already know Solidity and the standard EVM developer toolkits, try deploying a small test contract on Monad. Measure how quickly transactions go through and test parallel performance by sending multiple concurrent transactions.
4. Join the Community: Engaging with the Monad community (Discord, Twitter, etc.) is an excellent way to learn best practices and get help if you run into any issues. You’ll also stay in the loop about new features or testnets.

Putting It All Together

Monad’s technology stack is a bold re-imagining of how EVM blockchains can run:

1. Consensus (MonadBFT) – A faster, leaner, two-phase BFT that achieves single-slot finality in about one second.
2. Asynchronous Execution – Consensus and execution are decoupled, so each block’s execution can use the full block time while the next block’s consensus runs in parallel.
3. Parallel Execution – By treating transactions more like a modern operating system, Monad executes many non-conflicting transactions at once, rescheduling conflicting ones only when needed.
4. MonadDB – A custom parallel-friendly database that helps ensure you’re not stuck waiting for single-threaded reads and writes.

By combining these four innovations, Monad is not just incrementally improving the EVM, but fundamentally redesigning the way it runs. The end goal is to allow dApps to scale on a single chain without insane fees or giving up on decentralization.

Conclusion

From a beginner’s perspective, it might seem like a bunch of technical jargon. But here’s the gist: Monad is trying to unleash the full power of the EVM by leveraging modern computing principles—parallel processing, asynchronous workflows, and a specialized database. That means faster transactions, cheaper fees, and a smoother experience for both developers and users.

For advanced readers who understand the limitations of current L1s and L2s, Monad’s approach to “accelerating, not bypassing” consensus, and “running transactions in parallel, not serially,” offers a new path forward. By designing their own chain from scratch, they avoid the constraints that come from relying on Ethereum’s block times, single-threaded execution, or centralized sequencers.

If you’re curious to learn more, be sure to check out Monad’s official website or their detailed blog posts on subjects like Monad vs. Rollups. And don’t forget to explore their community channels where you can follow updates, run a node, or chat with others about how to build dApps that take advantage of true parallel processing in the EVM world.

Thanks for reading! If you have any questions or comments, feel free to reach out—let’s keep the conversation going about how we can make blockchains faster, more scalable, and more fun to use.