🛣️ Parallelization Parallel Execution
A blockchain design that runs many independent transactions at the same time instead of one after another, so the network handles more activity, moves faster, and charges lower fees.
🛒 The simple version — checkout lanes
Picture a supermarket with a single open checkout. Every shopper waits in one line, paying one at a time. That's a sequential blockchain: transactions are processed in a single row, and when traffic spikes, the line gets long. Parallelization opens more lanes. Shoppers buying different things go through different lanes at the same time, so everyone finishes faster. The only catch: two people reaching for the exact same item still have to be sorted out in order.
⚙️ Why one-by-one becomes a bottleneck
Older blockchains like the original Ethereum EVM run every transaction one after another, in a strict line. That keeps things simple and predictable, but it wastes a modern computer. A processor has many cores that can work at the same time, yet a sequential chain uses them like a single worker. As demand grows, the line is the limit. Parallelization spreads independent transactions across those cores so they run together.
🔒 The catch — shared data must stay in order
Not everything can run at once. If two transactions touch the same account or smart contract (the same shared state), the order matters: who paid first, what the balance was. Those have to be handled in sequence so the network keeps one agreed-upon result. Only non-conflicting transactions, ones touching different data, truly run in parallel.
🗺️ Two ways chains do it
| Approach | How it works | Used by |
|---|---|---|
| 🎲 Optimistic | Assume nothing conflicts, run everything in parallel, then re-run the few that clashed in order | Monad, Sei v2, Aptos (Block-STM) |
| 📋 State-access | Each transaction declares upfront which data it reads and writes, so the system safely groups what can run together | Solana (Sealevel) |
📊 Marketing often cites huge multiples like "100x faster." Treat exact numbers as vendor claims, not guarantees — real speed depends on the traffic and the test.
🪙 Where a beginner meets it
- ⚡ Solana (SOL) — its Sealevel runtime parallelizes by reading declared state dependencies
- 🧱 Aptos (APT) and Sui (SUI) — run independent transactions side by side
- 🟪 Monad (MON) and Sei (SEI) — bring parallel execution to EVM-style chains
- 🧠 Why it matters — faster processing, higher throughput, better scalability, and lower gas fees
❓ FAQ
- Does parallelization mean every transaction runs at the same time?
- No. Only transactions that don't touch the same data can run side by side. If two transactions both change the same account or smart contract, the chain still has to run them in order so everyone agrees on one final result.
- Is a parallel chain always faster than a sequential one?
- Usually for everyday traffic, yes, because most transactions are independent. But parallel execution is only one part of the system. Other limits like consensus, networking, and how fast the chain can read its own state still apply, so 'infinite speed' claims are marketing, not a guarantee.
- Which coins actually use parallelization?
- Solana runs transactions in parallel by asking each one to declare upfront which data it touches. Aptos and Sui run independent transactions side by side and sort out conflicts afterward. Monad and Sei bring parallel execution to EVM-style chains.