Can You Explain How Rollups or Sidechains Differ From Purpose‑Built Real‑Time Settlement Platforms in Terms of Throughput and Cost? With Examples and Benchmarks

Short summary: Rollups and sidechains lower costs by externalizing data and/or security, but their throughput and finality are bounded by their base layers and DA choices; purpose‑built real‑time L1s trade Ethereum-inherited security for sub‑second settlement and ultra‑low fees. Below we quantify the trade‑offs with fresh benchmarks, concrete cost math, and deployment patterns you can use today.

Who this is for

Decision‑makers at startups and enterprises evaluating where to build high‑volume, latency‑sensitive apps (payments, trading, loyalty/micropayments, gaming, supply chain), and needing crisp, current numbers rather than marketing claims.

TL;DR benchmarks (December 2025 snapshot)

Optimistic rollups (OP Stack chains like Base, OP Mainnet): 2s blocks today, 1s feasible; ≈32.5M L2 gas/sec observed on Base; that’s roughly 1,550 simple transfers/sec or ~325 medium swaps/sec. Fees commonly ≈$0.005–$0.05 post‑EIP‑4844, but vary with L1 blob price. (docs.optimism.io)
ZK rollups: faster L1 finality per proof batch; user fees down sharply after 4844; proof costs/latency depend on circuits and batching policy. (ethereum.org)
Sidechains (Polygon PoS, Gnosis): deterministic finality ≈2–5s on Polygon PoS after 2025 upgrades; typical fees ≪$0.01; throughput targets 1,000+ TPS live (Polygon), scaling higher through 2025, but security is independent from Ethereum L1. (docs.polygon.technology)
Purpose‑built real‑time L1s (Solana, Sei, Sui, Aptos): sub‑second finality by design; base fees ≪$0.01, often $0.0005–$0.005; built for parallel execution and low latency; best for HFT‑like UX. (solana.com)

1) What exactly are we comparing?

Throughput: how many state changes/txs per second your app can actually get included and finalized at your target latency.
Cost: end‑user fee per transaction and total cost drivers (data availability, proofs, priority fees, validator economics).
Finality/settlement: time until a transaction is economically irreversible for your business logic.

Why this matters: Batch‑based scaling (rollups) and non‑Ethereum security (sidechains) keep costs low, but they don’t inherently deliver sub‑second, globally consistent settlement under peak load. Purpose‑built real‑time L1s were engineered around parallelism and fast BFT pipelines for that exact outcome.

2) Rollups in 2025: what changed after EIP‑4844 (Dencun)

EIP‑4844 added “blob” space to Ethereum (target three blobs per block; max six; 128 KiB each; ~18‑day retention). Rollups publish data to blob space instead of permanent calldata, cutting L2 data costs by an order of magnitude and relieving long‑term state growth. Mainnet activation: March 13, 2024 (epoch 269,568). (ethereum.org)
Concrete fee impact: Following Dencun, average L2 fees dropped sharply (e.g., Optimism and Base into low cents; Arbitrum lower but more variable). Measured reductions span 10–100x depending on blob price/weather; press and on‑chain analytics documented multi‑x declines in March–April 2024. (coindesk.com)

Throughput reality on OP‑stack rollups:

OP Stack “Superchain” fact sheet lists throughput ≈32.5M L2 gas/sec (from Base measurements). At 21,000 gas for a simple transfer, that’s ≈1,547 transfers/sec. At ~100,000 gas for a mid‑complexity swap, ≈325 swaps/sec. Sequencer block time is 2s by default; research shows 1s blocks are achievable under production loads with current hardware. (docs.optimism.io)

Finality/withdrawals:

Optimistic rollups: near‑instant L2 confirmations for UX, but canonical L1 settlement includes a 7‑day dispute window for withdrawals. Good bridges/liquidity networks hide this for users moving back to L1. (coinmarketcap.com)
ZK rollups: validity proofs give faster L1 finality per submitted proof; effective “final” timing depends on your rollup’s proof‑posting cadence (often minutes). (ethereum.org)

Hidden costs to model:

DA volatility: blob price is its own fee market; spikes when many rollups compete for the same blob space. (ethereum.org)
Prover costs (ZK): GPU/ASIC time and engineering complexity—amortized via batching/recursion. (Vendor‑specific, but material in budgets.) (ethereum.org)
Sequencer economics: margins vary by chain; some rollups keep a spread between user fees and L1 costs. (Example press coverage discussed Base’s economics around L1 settlement share.) (coinlive.com)

Practical example:

A consumer app doing 25 million monthly simple transfers needs ~9.6 TPS sustained. Any mainstream rollup easily handles this and, post‑4844, keeps median fees in low cents. However, if you require sub‑second L1 finality or consistent <500 ms end‑to‑end latency, you’re outside optimistic rollups’ comfort zone and into ZK rollups or real‑time L1 territory. (ethereum.org)

3) Sidechains: cost‑efficient throughput, independent security

Polygon PoS and Gnosis Chain exemplify the “EVM sidechain” model—fast blocks, low fees, their own validator sets and economics.

Polygon PoS:
- 2025 upgrades (Bhilai/Gigagas) targeted and then delivered live 1,000+ TPS capacity with roadmap to 5,000 TPS and lower finality; Polygon communicates deterministic finality ~2–5s with Heimdall v2 and follow‑on upgrades. Typical user fees remain well under a cent for common actions. (polygon.technology)
- Live gas tracker regularly shows <$0.01 per ERC‑20 transfer/swap in normal conditions. (polygonscan.com)
Gnosis Chain: typically low fees with ~5s block times; optimized for predictable, cheap transactions using xDAI. (Enterprises often like its fee predictability.) (gnosisscan.io)

Caveat to plan for:

Sidechains don’t inherit Ethereum’s security. You gain speed and cost but assume the chain’s validator/bridge trust model. Also, finality incidents—while rare—can happen; Polygon acknowledged a temporary 10–15 minute finality delay in Sept 2025 during a milestone issue (blocks kept producing; finality lagged). Build operational playbooks for these tail events. (theblock.co)

When to choose:

You need EVM, ultra‑low fees, seconds‑level finality, and tighter control of governance/economics than a shared rollup, and you accept the independent security model and bridge trust.

4) Purpose‑built real‑time settlement L1s: engineered for sub‑second finality

These chains make fast, parallel execution and immediate finality the primary objective—ideal for real‑time payments, orderbooks, games, and streaming commerce.

Solana
- Slots target ~~400 ms; confirmations typically sub‑second in practice. Fees are a flat 5,000 lamports per signature (~~$0.0005 at $100/SOL), with optional priority fees that can dominate during congestion; local fee markets and priority fees let urgent txs land quickly. (galaxy.com)
- For latency‑sensitive flows (CLOBs, arbitrage), builders integrate Jito bundles and low‑latency send to guarantee atomicity/fast landing via tip auctions. Budget small tips in your fee model. (jito-foundation.gitbook.io)
Sei (Twin Turbo consensus)
- Aggressively tuned BFT with pipelining and optimistic execution targets ≈400 ms block time; designed for responsive CLOB/exchange‑style apps (EVM support in v2). (docs.sei.io)
Sui (Mysticeti)
- DAG‑based consensus optimized for parallelism; mainnet time‑to‑finality typically ~480–550 ms in performance testing; object‑centric execution favors parallel workloads (airdrops, games). (docs.sui.io)
Aptos (Zaptos/Raptr research)
- Recent peer‑reviewed results show 20k TPS with sub‑second latency in geo‑distributed tests, with roadmap work (Raptr/Prefix consensus) pushing high throughput and low latency simultaneously. Treat as “engineering headroom” more than an always‑on mainnet promise, but it’s a strong indicator. (arxiv.org)

Cost profile:

These chains typically charge fractions of a cent per tx at scale. On Solana, baseline ≈$0.0005 plus any priority fee; even if you average $0.001–$0.003 including priority tips, 1 million transactions cost ≈$1,000–$3,000—orders of magnitude below most L2s during busy blob markets. (solana.com)

Trade‑off:

You don’t inherit Ethereum’s settlement guarantees; bridging to/from Ethereum means additional trust assumptions and operational risk. The payoff is consistent sub‑second UX and extremely low marginal cost per tx.

5) Data availability (DA) choices: a quiet but decisive cost lever for rollups

Ethereum blobs (EIP‑4844): 128 KiB per blob, up to 6 per 12‑second slot; blob data pruned after ~18 days; distinct blob gas market avoids competing with EVM gas. Post‑Dencun, most rollups saw double‑digit x fee reductions. (eips.ethereum.org)
Alternative DA layers: If your rollup posts to Celestia (often via Conduit), DA can be pennies per MB—especially with “SuperBlobs”—materially undercutting Ethereum blob $/MB under typical conditions. Measured case studies report sub‑$1/MB on SuperBlobs windows; real‑time prices vary. (conduit.xyz)

Implication:

A rollup’s all‑in user fee = (DA cost + execution cost + margin)/tx. DA dominates for data‑heavy apps. If your protocol emits large state diffs (e.g., orderbooks, frequent price updates), modeling DA $/MB variability and batching strategy is essential to keeping unit costs predictable. (ethereum.org)

6) Worked comparisons (decision‑grade)

Note: These are conservative, engineering‑oriented estimates using public docs/measurements. Always test with your exact tx sizes and patterns.

Medium‑complexity DeFi swap at scale

OP‑stack rollup (Base/OP): ~100k gas/tx → capacity ≈325 swaps/sec at 32.5M gas/sec; fee commonly ~$0.01–$0.05 post‑4844 in normal blob markets. Great fit if seconds‑level confirmation is fine; ZK rollups can speed L1 finality. (docs.optimism.io)
Solana: Sub‑second inclusion; fee ≈$0.0005 base + priority if needed. Suits real‑time trading UX and order‑routing where latency arbitrage matters. (solana.com)
Polygon PoS: 1,000+ TPS live; fees ≪$0.01; finality a few seconds. Strong EVM option when you need consistent pennies‑level UX and very high headroom without L1 blob exposure. (polygon.technology)

Micropayments/loyalty (100M tx/month; SLA: “final in <1s; fee <$0.002”)

Rollups hit fee targets most days after 4844 but struggle to guarantee sub‑second finality at L1 and may breach $0.002 when blob prices spike. (ethereum.org)
Solana/Sei/Sui meet both latency and fee constraints with room to spare, with the trade‑off of non‑Ethereum security. (solana.com)

Enterprise payments rail (cost predictability, deterministic finality)

Polygon PoS now advertises deterministic finality in ~2–5s and sub‑cent fees; that predictability is valuable for treasury processes. Monitor network status and design for rare finality incidents (e.g., Sept 2025 delay). (docs.polygon.technology)

7) Emerging best practices we implement for clients

On rollups (OP/ZK):

Right‑size batch cadence vs. latency: Increase blocks/batches at peak to amortize DA costs while keeping UX snappy; drop to longer batches off‑peak to maximize compression. Monitor blob base fee and autoscale the batcher. (ethereum.org)
Keep tx gas under “sweet spots”: On OP‑stack, staying below ~120k gas/tx increases effective TPS within the 32.5M gas/sec budget. Use calldata minimization, calldata‑to‑blob migration, and event packing. (docs.optimism.io)
DA diversification: If your unit economics are DA‑heavy, prototype Celestia/EigenDA variants; Conduit’s SuperBlobs have demonstrated sub‑$1/MB windows—big savings for orderflow‑heavy apps. (conduit.xyz)
Exit UX: For optimistic rollups, integrate instant withdrawal liquidity providers and prove‑on‑demand bridges so users never experience the 7‑day window. (coinmarketcap.com)

On sidechains:

Finality and incident drills: Add a “finality buffer” in payments (e.g., post funds available on app at T+N blocks), and build a circuit breaker for anomalous time‑to‑finality spikes like the Sept 2025 Polygon incident. (theblock.co)
Price hygiene: Pin gas to <$0.01 by monitoring chain gas oracles; pre‑fund fee wallets for a quarter of run‑rate txs to avoid fee shocks. (polygonscan.com)

On real‑time L1s (Solana/Sei/Sui/Aptos):

Plan for priority fees under load: On Solana, most fee outlay during congestion is priority. Budget a small tip (e.g., $0.0005–$0.003) for latency‑critical flows to ensure landing; use Jito bundles for atomic multi‑tx sequences. (galaxy.com)
Parallelism‑friendly design: Batch independent writes; on Sui, leverage object‑centric patterns to maximize parallel execution and keep tail latency low. (docs.sui.io)
Observability: Track slot times, failed tx ratio, and bundle landing latency; alert on drift from your SLA.

Cross‑chain architecture:

If you want Ethereum settlement AND sub‑second UX, build a real‑time L1 front‑end plus periodic settlement to an L2 (e.g., anchor daily state roots) or deploy a ZK rollup and tune proof cycles for near‑real‑time settlement. Cost model must include DA on Ethereum or Celestia and operational costs of proofs. (ethereum.org)

8) Cost planning cheat‑sheet (ballpark; benchmark your own txs)

Rollups after 4844:
- Typical user fees: ~$0.005–$0.05 in calm markets for common interactions; can spike with blob demand. A million txs ≈ $5k–$50k. (coindesk.com)
Sidechains (Polygon PoS):
- Often <$0.003 per transfer/swap; a million txs ~ up to a few thousand dollars; finality ≈2–5s. (polygonscan.com)
Real‑time L1s (Solana):
- ≈$0.0005 base + optional priority tips; a million txs ≈ $500–$3,000 depending on your urgency mix. (solana.com)

9) Throughput planning cheat‑sheet

OP‑stack today: design around ≈1,500 simple transfers/sec or ≈325 medium swaps/sec at Base‑like capacity; 1s blocks are viable with tested node hardware, increasing headroom for interactive UX. If you need more, spin an app‑specific OP chain or shard by function. (docs.optimism.io)
Polygon PoS: 1,000+ TPS live in 2025 upgrades with targets rising; robust for EVM workloads needing cheap, high volume with seconds‑level finality. (polygon.technology)
Solana/Sei/Sui/Aptos: assume sub‑second confirmation targets and tune app logic for parallel execution to exploit chain‑level parallelism; account for priority fee markets during bursts. (solana.com)

10) Choosing the right fit: a simple rubric

You need sub‑second, exchange‑like UX and <$0.002 fees: favor Solana/Sei/Sui; bridge or periodically settle to Ethereum if needed. (solana.com)
You need Ethereum security, low fees, and can live with seconds‑level UX: use an OP‑stack or ZK rollup; pick DA (Ethereum blobs vs Celestia) based on $/MB and your data footprint. (ethereum.org)
You need predictable fees, EVM, and infra control with fast but not sub‑second finality: a sidechain like Polygon PoS is pragmatic; invest in finality monitoring. (docs.polygon.technology)

11) What we advise teams to benchmark before committing

End‑to‑end latency distribution (p50/p95) from wallet click to confirmed state your app depends on.
Unit economics at your expected average tx size and write frequency, including DA $/MB and priority fees.
Degradation under blob spikes (rollups) or priority fee surges (Solana), and under finality hiccups (sidechains).
Operational levers: batch size, proof cadence, Jito tips, gas oracles, and autoscaling of sequencers/indexers.

If you want a numbers‑first architecture review or a POC that measures these metrics for your exact tx mix, 7Block Labs can stand up comparative test harnesses on the chains above and produce a vendor‑neutral recommendation.

References

Dencun/EIP‑4844 overview, blob sizes, retention, and activation details. (ethereum.org)
OP Stack throughput and block‑time research (Base). (docs.optimism.io)
L2 fee reductions after Dencun (examples across OP/Base/Arbitrum). (coindesk.com)
Polygon PoS finality and 2025 throughput upgrades; fee snapshots. (docs.polygon.technology)
Solana fee model, slot/confirmation behavior, and Jito bundles. (solana.com)
Sei Twin Turbo consensus (≈400 ms target). (docs.sei.io)
Sui Mysticeti performance/finality. (docs.sui.io)
Aptos Zaptos latency/throughput (2025). (arxiv.org)
Celestia SuperBlobs vs Ethereum blobs (DA cost comparisons). (conduit.xyz)