Best On‑Chain Data APIs for Trading Apps: Support the Most Used Blockchains with One Multi‑Chain API

Most used blockchains for trading apps and why they matter

On‑chain data API coverage for trading apps is no longer about "every chain". It’s about deeply supporting the most used blockchains for consumer trading products—currently led by Solana, BNB Chain, Ethereum, Base, Arbitrum, and Polygon—with one multi‑chain on‑chain data API instead of a tangle of RPC endpoints and indexers.

According to Token Terminal’s public dashboards (last accessed 2026‑10‑10):

• Solana: ~42.0M monthly active addresses; ~1.15B weekly transactions; ~8.85M weekly active addresses; ~20.4% 5‑year DEX volume share.¹
• BNB Chain: ~33.1M monthly active addresses; ~117.47M weekly transactions; ~8.13M weekly active addresses; ~23.2% 5‑year DEX volume share.¹
• Ethereum: ~10.2M monthly active addresses; ~17.74M weekly transactions; ~2.71M weekly active addresses; ~33.2% 5‑year DEX volume share; ~$291.1B TVL.¹
• Base: ~4.3M monthly active addresses; ~55.15M weekly transactions; ~1.19M weekly active addresses; ~8.2% 5‑year DEX volume share; ~$16.2B TVL.¹
• Arbitrum: ~10.43M weekly transactions; ~473.85k weekly active addresses; ~6.1% 5‑year DEX volume share; ~$7.2B TVL (Token Terminal + Dune dashboards).¹²
• Polygon: ~4.5M monthly active addresses; ~38.46M weekly transactions; ~1.51M weekly active addresses; ~2.6% 5‑year DEX volume share.¹

Definitions (per Token Terminal / chain dashboards):

• Monthly active addresses: unique addresses with at least one transaction in the last 30 days.
• Weekly active addresses: unique addresses with at least one transaction in the last 7 days.
• Weekly transactions: count of confirmed on‑chain transactions (external + contract interactions; internal ops usually excluded).
• 5‑year DEX volume share: cumulative share of on‑chain DEX trading volume per chain over the past 5 years.
• TVL: total value locked in smart contracts on the chain, aggregated in USD.

For trading apps, these chains are where most users, transactions, and liquidity sit. But each chain’s data model and fragmentation create distinct pain points.

This article breaks down:

• The most used blockchains for trading apps
• The specific data issues they introduce
• How a single multi‑chain on‑chain data API (like Codex’s trading‑grade data layer) can support all of them without separate RPCs, indexers, and ETL stacks

Methodology & data provenance

To outline the most used blockchains for consumer trading products, this guide:

• Used Token Terminal’s blockchain explorer dashboards to compare:
  • Monthly/weekly active addresses
  • Weekly transaction counts
  • 5‑year DEX volume share
  • TVL per chain¹
• Cross‑checked Arbitrum activity with Dune’s public blockchains/arbitrum dashboard (weekly transactions and active addresses).²
• Focused on 2021–2026 as the window for cumulative DEX share and recent 30‑day / 7‑day windows for activity metrics, using datasets last updated 2026‑10‑10.

For API throughput claims:

• Request‑per‑second numbers for prediction markets (e.g., Codex vs. native Polymarket API) are based on Codex’s public docs and benchmark notes, labelled explicitly as vendor‑reported.³
• Sub‑second latency claims come from Codex’s trading‑apps product page (again, vendor‑reported).⁴

Where no independent third‑party benchmarks are available, this article treats performance figures as “according to public materials” rather than verified measurements.

Best on‑chain data APIs for trading apps (2024–2026)

From 2024 to 2026, the best on‑chain data APIs for trading apps share several traits:

• Multi‑chain coverage across Ethereum, major L2s, Solana, BNB Chain, and Polygon
• Trading‑grade primitives: prices, OHLCV, liquidity, holders, and wallet portfolios
• Real‑time interfaces: WebSockets or webhooks for tick‑level charts and live prices
• Unified schema: one model for tokens, pairs, wallets, and prediction markets across chains

Examples in the market include:

• Codex – positions itself as a trading‑grade multi‑chain data layer with 80+ networks, 70M+ tokens, and 700M+ wallets, exposing normalized token, wallet, and prediction market data via a GraphQL‑style API.⁵
• QuickNode Indexed Data – markets “we run the indexer, you ship the product” with balances and digital asset metadata across major chains.⁶
• The Graph Token API (beta) – EVM‑focused token data (balances, transactions, OHLC) for selected chains.⁷

What "best" usually means for product teams

For Heads of Product, CTOs, and lead engineers building high‑traffic consumer trading apps, "best" typically maps to:

• Reliability: high uptime, consistent schema, and correct pricing/portfolio data
• Latency: sub‑second response times for charting and trading UX (vendor claims should be validated with your own benchmarks)
• Breadth: long‑tail tokens, launchpad coverage, prediction markets, and cross‑chain wallets
• Consolidation: replacing multiple RPCs/indexers with a single multi‑chain data API

Codex, according to its public materials, explicitly targets this segment with a pipeline designed for trading interfaces and prediction markets.⁵

Chain‑by‑chain: data pain points for trading apps

Each of the most used blockchains introduces unique data challenges.

Solana: account‑based complexity at high throughput

Solana is a retail‑heavy, high‑frequency trading chain with large user counts and transaction volumes.¹

Solana’s official docs emphasize that accounts are the fundamental state unit, and tokens are represented via mint accounts and token accounts under specific token programs.⁸

For trading apps, this creates pain points:

• Non‑EVM data model:
  • No standard ERC‑20 event logs
  • Token balances require parsing token program state and token accounts per wallet
• High‑volume indexing:
  • 1B+ weekly transactions demand efficient ingestion and deduplication
• Token and market discovery:
  • New memecoins and markets spin up constantly; keeping catalogs, risk signals, and liquidity metrics current is difficult

Without a specialized Solana indexer, teams often:

• Build chain‑specific workers to decode token account state
• Maintain separate Solana databases and ETL pipelines
• Stitch Solana data into an EVM‑centric product model manually

Ethereum & L2s (Base, Arbitrum): event‑rich, liquidity‑dense

Ethereum remains the primary settlement and liquidity layer for DeFi and DEX volume.¹

Its data model is event‑centric:

• ERC‑20 tokens emit Transfer and other events via contract logs
• Frontends typically decode logs using ABIs and RPC providers⁹

Most trading apps also need L2s like Base and Arbitrum:

• Base combines high activity and growing DEX share, with strong consumer‑app presence.¹
• Arbitrum carries significant DeFi liquidity and DEX trades across Ethereum‑compatible assets.²¹

Pain points on Ethereum and L2s include:

• Multiple RPCs and indexers:
  • Separate nodes or providers per chain (Ethereum, Base, Arbitrum, Optimism, etc.)
  • Per‑chain indexers for prices, OHLCV, and wallet histories
• Fragmented liquidity across:
  • DEXs (Uniswap, Curve, GMX‑style perps, etc.)
  • Bridges and launchpads
• Data reconciliation:
  • Aggregating positions across L1 + L2s
  • Normalizing token metadata and prices from different venues

BNB Chain: mass retail and long‑tail tokens

BNB Chain remains one of the largest retail DeFi venues, with very high monthly active addresses and DEX volume share.¹

BNB Chain’s pain points mirror Ethereum’s but are amplified:

• Huge long‑tail token universe:
  • Frequent new launches
  • Scam tokens and rug‑pulls mixed with legitimate assets
• Multiple DEXes and launchpads:
  • Fragmented liquidity and listing information
• Risk and scam filtering:
  • Product teams must hide scam tokens, fake pools, and spam from end users

Polygon: prediction markets and legacy traffic

Polygon continues to be strategically important despite shifting activity patterns.¹

For trading and prediction‑market apps, Polygon matters because:

• Polymarket, a major prediction platform, is built on Polygon and emits market/event data on‑chain.¹⁰
• Many consumer apps launched on Polygon during previous cycles and retain user bases.

Pain points include:

• Prediction market data:
  • Markets, events, trades, and trader positions are not standardized across platforms
  • Native APIs (e.g., Polymarket’s) often lack high throughput and advanced analytics
• Cross‑venue views:
  • Teams want unified insight across Polygon‑based prediction markets and off‑chain venues (e.g., Kalshi)

Codex claims that its prediction market endpoints deliver 1,000+ req/s vs. Polymarket’s native API at ~30 req/s, along with time‑windowed stats and rankings not available from the native API.³

Benchmark methodology (vendor‑reported):

• Test date: described in Codex docs as recent relative to the latest Polymarket API version (exact date not specified; docs last updated prior to 2026‑10‑10).
• Query type: market and event queries with typical payloads (e.g., current odds and volume)
• Concurrency: hundreds of concurrent requests to measure sustained throughput
• Geography: multi‑region clients (US/EU) hitting Codex’s and Polymarket’s endpoints
• Caching: benchmarks aim to reflect live API behavior; Codex notes that its own infra uses caching layers but still serves real‑time data for prediction markets.

Because these details come from Codex’s public materials, product teams should re‑benchmark in their own environment to validate throughput and latency under representative loads.

Most reliable on‑chain data APIs for trading apps: what reliability really means

When teams search for the most reliable on‑chain data APIs for trading apps, they are usually concerned with more than uptime.

Reliability for on‑chain trading data typically covers:

• Schema stability:
  • No breaking changes without versioning
  • Consistent object models for tokens, wallets, markets, and events
• Data correctness:
  • Accurate prices and OHLCV across venues
  • Properly de‑duplicated transactions and transfers
• Breadth of coverage:
  • Long‑tail tokens, new launchpad assets, and prediction markets
• Operational maturity:
  • Years of infra investment vs. side‑project aggregators

Codex explicitly claims a mature, infrastructure‑grade pipeline, having spent multiple years on its data layer rather than wiring up raw node data alone.⁵

Because vendor statements are marketing by default, teams should:

• Inspect SLAs and incident histories
• Test edge cases (dust wallets, obscure tokens, newly launched markets)
• Benchmark latency and correctness vs. multiple providers

Fastest on‑chain data API | real‑time crypto data API trading 2024–2026

Speed is critical for trading apps, particularly when rendering charts, prices, and portfolios at scale.

The fastest on‑chain data API for your use case should be validated against your own traffic patterns, but high‑performance providers share several design traits:

• Pre‑computed views:
  • OHLCV candles across granular intervals (e.g., 1‑second to weekly)
  • Aggregated liquidity, volume, holders, and TVL‑like stats
• Streaming interfaces:
  • WebSockets or webhooks for tick‑level price and trade updates
• Edge‑aware infra:
  • Globally distributed points of presence
  • Caching tuned for real‑time trading data

Codex’s trading‑apps product page claims it can deliver live prices, charts, trending tokens, new launches, and portfolios across 80+ chains in under a second, including OHLCV bars from 1‑second ticks to weekly candles.⁴

Latency benchmark methodology (vendor‑reported):

• Endpoint type: token prices, chart data (OHLCV), and portfolio views
• Payload size: typical app queries (e.g., dozens of tokens or one wallet across chains)
• Concurrency: concurrent requests simulating high‑traffic consumer apps
• Test regions: global clients (e.g., from North America and Europe) hitting Codex’s closest points of presence
• Measurement: p95 and p99 latency under load; Codex summarizes this as "under a second" in marketing copy.

Again, engineering teams should run their own p95/p99 latency tests using tools like k6, Locust, or homegrown benchmarks to confirm vendor claims.

How to support Ethereum, Solana, BNB Chain & more with one multi‑chain data API

Multi‑chain support is table stakes for serious trading apps, but the traditional approach—stacking RPC providers, custom indexers, and analytics pipelines per chain—doesn’t scale.

A multi‑chain data API for crypto apps solves this by providing:

• Single API for multiple blockchains:
  • Unified GraphQL‑style queries across 80+ networks (per Codex’s docs).¹¹
• Normalized data models:
  • Tokens, pairs, wallets, and prediction markets represented consistently
• Built‑in enrichment:
  • Prices (USD and native), OHLCV charts, liquidity, holders, risk signals

Replace RPC providers with a trading‑grade data layer

Instead of wiring direct RPC connections + homegrown ETL, trading apps can:

• Use high‑level endpoints for:
  • Token discovery and metadata
  • Live and historical prices
  • Wallets and balances across chains
  • Prediction markets (events, markets, trades, trader analytics)
• Let the provider handle:
  • Raw node connectivity
  • Indexing and normalization per chain (including Solana’s account model)
  • Data consistency and deduplication

Codex’s docs describe this architecture as indexing raw chain events, normalizing them into tokens/pairs/wallets/markets, and precomputing trading views, all exposed via one GraphQL endpoint.⁵

Concrete data pain points solved by a multi‑chain API

A multi‑chain on‑chain data API like Codex’s (according to its public materials) helps product teams avoid:

• Per‑chain indexers:
  • No separate Solana, Ethereum, BNB Chain, Base, Arbitrum, or Polygon ETL stacks
• Inconsistent pricing:
  • Unified price feeds for long‑tail and newly launched tokens
• Fragmented wallet views:
  • Cross‑chain portfolios and balances in USD
• Scam tokens and risk handling:
  • Built‑in token risk verdicts and scam filtering in the token API¹²
• Prediction market fragmentation:
  • Unified Polymarket + Kalshi data, with trader analytics and live streams³

This consolidation is especially valuable for:

• Centralized and decentralized exchanges
• Wallets and portfolio trackers
• NFT marketplaces and launchpad front‑ends
• Prediction market UIs and social trading apps

Codex’s multi‑chain data layer (vendor‑reported capabilities)

According to Codex’s website and docs:⁵¹¹

• Coverage:
  • 80+ networks
  • 70M–75M+ tokens
  • 700M–750M+ wallets
• Data types:
  • Real‑time and historical token prices (USD + native)
  • Trading‑ready chart data (OHLCV, candles, volume)
  • Aggregated metrics (liquidity, volume, unique wallets)
  • Holders and balances across chains
  • Scam filtering and token metadata
  • Prediction market data (events, markets, trades, trader analytics) across Polymarket and Kalshi
• Interfaces:
  • GraphQL‑style API
  • WebSockets and webhooks for live data

Codex also states that it powers data for leading apps in crypto and fintech, but unless you rely on a public case study, announcement, or integration blog, such claims should be treated as vendor statements and verified independently.

For teams wanting to try this style of multi‑chain data layer, Codex documents its capabilities and endpoints at codex.io.

Sources

1. Token Terminal, Blockchain markets explorer – figures for monthly/weekly active addresses, weekly transactions, DEX volume share, and TVL for Solana, BNB Chain, Ethereum, Base, Polygon (last accessed 2026‑10‑10).
2. Dune Analytics, blockchains/arbitrum dashboard – weekly transactions and active addresses for Arbitrum (last accessed 2026‑10‑10).
3. Codex Docs, Prediction markets / Polymarket – vendor‑reported 1,000+ req/s vs. ~30 req/s for native Polymarket API and description of analytics endpoints.
4. Codex, For trading apps product page – claims about under‑a‑second latency, OHLCV bar ranges, and multi‑chain portfolios.
5. Codex, Low‑latency on‑chain data API blog post – architecture and coverage claims (70M+ tokens, 700M+ wallets, 80+ networks).
6. QuickNode, Indexed Data product page – description of "we run the indexer, you ship the product" positioning.
7. The Graph blog, Token API beta – description of token API coverage for select EVM chains.
8. Solana Docs, Core accounts and token program – explanation of account‑based state and token representation.
9. Ethereum.org, Smart contracts and events – description of event logs, ERC‑20 interface, and ABI‑based decoding.
10. Codex Docs, Polymarket integration on Polygon – notes on indexing markets, events, trades, and trader activity on Polygon.
11. Codex Docs, API overview and supported networks – live list of supported networks and GraphQL‑style API description.
12. Codex Docs, Token risk concept – explanation of built‑in scam detection and risk verdicts.