Solana: Pros and Cons of Deploying Smart Contracts

Solana is built for high-frequency onchain activity, not just cheap settlement

Solana is a single-state-machine blockchain built around Proof of History, parallel execution, and aggressive throughput design rather than sharding. In the original architecture paper, Solana analyzed performance on a 1 Gbps network and described up to 710,000 transactions per second as a theoretical upper bound with then-current hardware. That number is best read as a design ceiling, not a live-network promise, but it captures the point: Solana was engineered for markets, payments, and other workloads where state changes arrive continuously and latency matters.

For smart contract teams, the practical consequence is simple. Solana is not trying to be the easiest chain to reason about. It is trying to be the chain where frequent writes, short feedback loops, and dense transaction flow are economically viable. Solana’s own developer docs frame the network around accounts, programs, instructions, transactions, and fees, with programs compiled to sBPF, state stored in accounts, and a maximum transaction size of 1,232 bytes.

That architecture makes Solana unusually attractive for order books, AMMs, perpetuals, payment rails, consumer apps, games, and DePIN systems that produce many small state transitions. It also means deployment quality depends less on a static “low fees” narrative and more on how your app interacts with hot accounts, local fee markets, RPC infrastructure, and transaction landing under stress. Solana itself explicitly uses local fee markets, where transactions compete primarily with other traffic touching the same state.

Solana’s technical history matters because its trade-offs were tested in production

Solana Mainnet Beta launched on March 16, 2020. By the end of 2020, Solana was already describing Proof of History, Sealevel, Turbine, and Cloudbreak as the core architectural innovations behind the chain’s performance model.

That early design was powerful, but it was not frictionless. On April 30, 2022, Solana’s mainnet beta stalled for about seven hours after an inbound flood of roughly 6 million transactions per second and more than 100 Gbps of traffic at individual nodes. The proximate cause was not a generic market downturn. It was a market-structure event: bot competition around an NFT mint created an incentive to saturate the network with traffic, as Solana later detailed in its April 2022 outage report.

That episode is still analytically important. It showed that Solana’s strengths and weaknesses both emerge most clearly in bursty demand. The same architecture that supports dense transaction flow can also concentrate stress around specific accounts, programs, or event types. For anyone deploying smart contracts today, that is the right lens: not “is Solana fast?” but “what happens when everyone touches the same state at once?” The answer depends on account design, fee logic, and execution path more than on headline TPS. It is also the right way to frame a chain-selection exercise.

At the same time, the network’s resilience has improved materially. As of June 20, 2025, the network health report described 16 months of continuous uptime with no major network issues, alongside the release of Frankendancer and improved validator economics. That does not erase the outage history. It does show that the current version of Solana is more mature than the 2021-2023 caricature.

What deploying a smart contract on Solana actually requires

Deploying on Solana means learning a different execution model, not just a different SDK. A Solana smart contract is called a program. Programs are stateless executable accounts compiled to sBPF via LLVM, while all mutable state lives in separate data accounts passed into instructions. Most programs are written in Rust, typically with Anchor or native Rust.

The execution model is explicit about parallelism. Each instruction specifies the accounts it will read and write, and validators use that metadata to determine which transactions can run in parallel. Transactions that write to different accounts can execute in parallel. Transactions that contend for the same writable state cannot.

That is the most important technical fact to internalize before deployment. On Solana, performance is partly an application-level design problem. If your state layout creates hot accounts, you create your own fee spikes and your own latency. If your state layout shards cleanly, Solana’s parallel runtime works in your favor. The chain does not solve that for you automatically.

The strongest arguments for deploying on Solana are operational, not ideological

Solana is strongest when your application benefits from frequent onchain updates and low-latency confirmation. Solana’s payments documentation describes funds as secured in roughly 400 ms, and its transaction-confirmation guide describes slots as configured at about 400 ms, though actual slot time can fluctuate. That is a meaningful product advantage for consumer payments, trading, gaming, and stateful apps that need fast feedback.

Solana is also strong when unrelated workloads should not bid against each other. Local fee markets mean that a viral mint or hot DeFi venue does not automatically impose global fee inflation on every other application. From a market microstructure perspective, that is a major advantage. Narrative stability improves because chain-wide gas panic is reduced. Liquidity shocks still exist, but they are more localized around the programs and accounts that everyone is actually fighting over.

Solana is especially attractive for reusable financial primitives. The official Ethereum-to-Solana migration guide notes that, unlike ERC-20 style redeployments, token creation on Solana can use the existing Token Program rather than redeploying a new token contract each time. That reduces redundant contract surface and pushes teams toward shared infrastructure.

Fee structure is another real advantage, but only if you read it correctly. The base fee is fixed per signature, with 50% burned and 50% paid to the block-producing validator. Priority fees are optional and go 100% to the validator. For deployers, that means ordinary usage can remain predictable, while congestion is handled through explicit price discovery for scarce block space. In other words, when the market gets busy, you are participating in a localized execution auction rather than passively accepting a chain-wide gas regime.

Solana also supports unusually compact atomic workflows. A single transaction can contain multiple instructions, and programs can perform cross-program invocations. That matters for DeFi and market apps because routing, settlement, lending, and collateral updates can be composed into one atomic path instead of spread across multiple user actions.

The main reasons not to deploy on Solana are complexity, hotspot risk, and infrastructure burden

For teams accustomed to Ethereum deployment, Solana is harder when the goal is a simple port. The official docs are direct on this point: most Solana programs are written in Rust, state lives outside the program, and the account model is the central conceptual shift. Solidity instincts do not map cleanly. Anchor reduces boilerplate, but it does not remove the need to reason about accounts, signers, writable flags, PDAs, CPI depth, and state allocation.

The second big risk is account contention. Solana’s parallelism is real, but it is conditional. If many users repeatedly touch the same writable accounts, your application becomes a congestion hotspot. Local fee markets protect the rest of the network, but they do not protect your users from your own state design. This is the core trade-off between narrative stability and liquidity shocks on Solana: the chain can stay broadly cheap while your specific venue becomes expensive and hard to land into.

Transaction landing is a real engineering problem, not a wallet-side detail. Solana’s own Foundation wrote on March 15, 2024 that many applications still did not use priority fees correctly, which led to delayed or dropped transactions under heavy usage. Solana’s production-readiness guidance also recommends explicit compute estimation, priority fee logic, retry strategies, and non-public production RPC infrastructure.

Short transaction lifetime adds another UX constraint. A recent blockhash is only valid for about 60 to 90 seconds, and stale or lagging RPC views can easily produce blockhash errors or dropped transactions. That is manageable for power users and market bots. It is much more painful for consumer flows where users hesitate, switch wallets, or sign slowly.

Deployment operations are also sharper-edged than many teams expect. Solana’s own deployment guidance notes that large programs use buffer accounts, deployment is not atomic, interruptions may require recovery or closure of buffer accounts, and mainnet deployment wallets must fund rent-exempt minimums for program accounts. Upgrade authority choices are also governance choices. Leaving authority in place preserves flexibility. Revoking it increases credibility and immutability, but removes an escape hatch. That is one reason a token launch plan has to account for authority and upgrade decisions early.

Infrastructure requirements remain demanding. Anza’s validator guidance recommends at least a 2.8 GHz CPU with modern instruction support, 12 cores / 24 threads or more, 256 GB RAM or more, multiple NVMe SSDs, and at least 1 Gbit/s symmetric internet with 10 Gbit/s preferred for mainnet-beta. That does not mean Solana is centralized by definition, but it does mean decentralization should be discussed in the context of hardware and operational cost, not slogans.

Finally, Solana’s orderflow model is different. The Foundation’s EVM-to-SVM guide states that Solana does not use a public mempool in the Ethereum sense and instead forwards transactions to upcoming leaders. For trading apps, liquidation engines, and MEV-sensitive systems, that changes how execution quality is achieved. You do not just optimize gas. You optimize landing paths, leader access, bundles, and account contention.

Well-known projects on Solana show where the chain is most convincing

The strongest evidence for Solana as a deployment target is not a benchmark sheet. It is the mix of applications that have chosen to live there. The ecosystem is deepest where fast settlement, dense orderflow, and repeated state updates matter.

That pattern is telling. The best-known Solana deployments cluster around execution-heavy categories: swaps, perps, liquidity infrastructure, payments, and DePIN. If your application mostly needs passive storage, rare writes, and an EVM-first deployment path, Solana is often more machinery than you need. If your application lives or dies on execution quality, user-level latency, and repeated micro-interactions, Solana becomes much more compelling.

That is the practical conclusion FinDaS Tokenomics would use in a chain-selection exercise. Solana is a strong deployment target when token economy design is tightly coupled to live market behavior, liquidity routing, and transaction landing. It is a weaker target when the team mainly wants EVM familiarity or when the application cannot tolerate the engineering burden of hotspot management. In tokenomics consulting, that distinction matters more than generic claims about speed. The token economy only works if the execution environment can handle the way users, bots, and liquidity providers will actually behave.

This article is part of our Choosing The Right Blockchain series.