Enterprise Blockchain Indexing and Blockchain API Fast Data Retrieval: What Blockchain API Supports Fast Data Retrieval?

Decision-makers are asking one question again and again: how do we get blockchain data fast enough to power real products and analytics? This guide compares real-world options—RPC, indexing frameworks, managed query APIs, and data warehouses—so you can pick the fastest path for your use case, with concrete examples and emerging best practices backed by current docs and benchmarks.

Summary

Fast, reliable blockchain data retrieval comes from combining the right API surface (RPC vs. specialized query APIs), the right indexing engine (Substreams, Subsquid, GraphQL indexers), and the right delivery pattern (WebSocket streams, warehoused SQL, or GraphQL). As of January 2026, the stack that consistently delivers sub-second to low-seconds p95 uses parallelized indexing (Substreams or Squid), provider-level “pre-indexed” endpoints (Alchemy Transfers, Covalent), and chain-native indexers (Aptos, Sui), with careful handling of reorgs, archive queries, and log-range limits.

What does “fast” mean for enterprise blockchain data?

In practice, your SLOs should focus on p95 latency and end-to-end freshness:

Read-heavy APIs commonly target p95 under 300–500 ms; transactional/complex analytics in the 500–800 ms range, with p99 under ~1 s for most user-facing endpoints. These are general API targets teams benchmark against and then tune for their own domain. (accelq.com)
Freshness depends on chain finality and your ingestion path; parallel pipelines and push-based streams minimize backfill time versus RPC polling.

“Fast” is therefore a mix of transport latency, query complexity, data locality, and whether someone else has already done the indexing for you.

Four ways enterprises retrieve blockchain data (and when each is fast)

Direct RPC (JSON-RPC/WebSocket)

Best for: simple, recent state reads; mempool/real-time streams.
Why it’s fast: zero intermediary for latest state; WebSockets push new heads/logs (no polling). (docs.metamask.io)
Where it slows down: historical queries, traces, and wide log scans. Providers and clients recommend strict filters and short block ranges; some enforce range caps (e.g., 3k–20k blocks), and clients like Besu encourage bloom caching and max range caps. (docs.chainstack.com)

Specialized “pre-indexed” APIs from infrastructure providers

Best for: wallet histories, token/NFT portfolios, balance snapshots, decoded logs—without running your own indexer.
Why it’s fast: the provider runs large indexing jobs once; you query a precomputed dataset via a single call.
Examples with current claims and docs:
- Alchemy Transfers API: “100x faster than alternatives” to retrieve complete transfer history (external, internal, ERC20/721/1155) with pagination and page keys. Recent messaging also highlights up to 20x faster Solana archive data on their infra. (alchemy.com)
- QuickNode Token API: instant ERC‑20 metadata, balances, and transfer history—“no indexing required,” backed by billions of sifted logs. (quicknode.com)
- Infura archive access: out‑of‑the‑box archive nodes across major networks so methods like eth_getBalance at old blocks and eth_getStorageAt at historical heights are served quickly without your own archive node. (docs.metamask.io)
- Covalent Unified API: multi-chain historicals and decoded logs over 100–200+ chains, with “enterprise-grade performance” and full replicas advertised in ecosystem docs. (docs.arbitrum.io)

Dedicated indexing frameworks (you run them or use a managed host)

Best for: complex domain indexes, analytics features, or anything not covered by canned provider APIs.
Why it’s fast: modern stacks parallelize block processing and stream flat files instead of RPC polling, bringing sync time down by orders of magnitude.

Parallelized/streaming engines:
- The Graph Substreams: parallel back-processing of chain history using Firehose feeds; The Graph highlights “up to 72,000% faster than traditional RPCs,” with multi-sink delivery to Postgres/ClickHouse/Subgraph. (thegraph.com)
- Goldsky: managed subgraphs with rewritten RPC and autoscaling query layers; docs cite up to 6x faster subgraphs and 99.9%+ uptime; case study shows 10x faster indexing and 50x faster queries for a zkSync DEX migration. (docs.goldsky.com)
- Subsquid: batch ETL from a decentralized data lake (“Archive”) with Squid SDK; resources state 1k–50k blocks/sec indexing and near-zero cost batch access vs RPC. (docs.devsquid.net)
Chain-native indexers:
- Aptos Indexer: public GraphQL API and an SDK/processor path for custom pipelines; strong table indexing and Hasura GraphQL endpoints to serve historical and aggregate views quickly. (aptos.dev)
- Sui GraphQL + General-Purpose Indexer: a high-performance GraphQL service backed by parallel pipelines; note that Sui is deprecating JSON‑RPC in favor of gRPC/GraphQL by April 2026, incentivizing indexer adoption for fast, structured queries. (docs.sui.io)
- Solana Geyser plugins: stream accounts/transactions/slots directly from validators into Kafka/Postgres/QUIC services; this offloads heavy queries from RPC and delivers near‑real‑time ingestion at scale. (docs.solanalabs.com)

Analytical data warehouses and APIs (SQL-first)

Best for: cross-chain analytics, BI dashboards, ML, and heavy aggregations where seconds-level latency is acceptable.
Why it’s fast: columnar engines and pre-partitioned tables; server-side filtering/pagination; result caching.

Options and notes:
- Google BigQuery public crypto datasets: multi-chain coverage (Ethereum, Avalanche, Polygon, Optimism, Arbitrum, Tron, etc.) with first‑party “Google‑managed” Ethereum tables for curated event schemas. Be mindful that chain tables can have update lag (for example, community posts flagged a Solana lag in March–April 2025). (cloud.google.com)
- Dune Analytics API: programmatic access to 1+ PB of indexed multi-chain data; engine sizing and 30‑minute timeouts are documented; server-side filtering and pagination help keep large result sets fast to retrieve. (dune.com)
- Space and Time (Proof of SQL): ZK‑verified SQL with sub‑second proving benchmarks on 1M+ rows, targeting online latencies and enabling verifiable results to smart contracts; integrations with BigQuery and Chainlink are active. (spaceandtimefdn.github.io)

Why raw RPC alone is rarely the fastest for enterprises

Direct RPC is excellent for the latest block state and real-time subscriptions (eth_subscribe newHeads/logs), but it becomes slow and flaky when you:

Scan wide ranges via eth_getLogs. Providers and clients advise limiting ranges (e.g., 3k–10k blocks typical; some cap at 20k), filtering by address/topics, and paginating. Besu recommends enabling bloom cache and even setting rpc‑max‑logs‑range. (docs.chainstack.com)
Need historical state or traces (debug_traceTransaction, parity trace_*). These often require archive nodes; public shared endpoints can time out on large traces. (therpc.io)

For speed and reliability, enterprises shift expensive workloads to pre-indexed APIs, Substreams/Subsquid pipelines, or chain-native indexers.

Practical examples for fast retrieval

Complete transfer history for an EVM address in one call

Use Alchemy’s Transfers API to fetch external/internal ETH transfers and ERC20/721/1155 in a single request. It supports pagination via pageKey and maxCount. This avoids millions of eth_getLogs calls and delivers big latency/cost savings. (alchemy.com)
When to choose this: portfolio/statement features, AML heuristics, address activity feeds, customer support tools.

Near real-time Solana indexing with Geyser → Kafka → ClickHouse

Attach the official Postgres or community Kafka Geyser plugin to a validator; stream accounts, transactions, and slot status directly to your pipeline. This decouples hot ingestion from RPC and gives sub‑second visibility into high-frequency activity. (docs.solanalabs.com)
Add materialized views and windowed aggregates in ClickHouse for low-latency dashboards and alerting.

Rapid multi-chain wallet features without running nodes

Covalent API provides balances, transfers, holders, and decoded logs across 100–200+ networks via a single schema. Ideal for wallets and loyalty/RWA apps that need breadth and reasonable speed with minimal infra. (docs.arbitrum.io)

Sub‑minute backfills at scale with Substreams or Subsquid

For a DEX or NFT marketplace subgraph that took days to sync via RPC polling, switch to Firehose/Substreams (parallelized flat-file backprocessing) or Squid SDK with Archive. Teams report order‑of‑magnitude speedups; The Graph advertises up to 72,000% faster backprocessing and multi-sink outputs, while Subsquid literature cites 1k–50k blocks/sec. (thegraph.com)

Queryable, auditable analytics via Dune or BigQuery

Move your heaviest aggregations to Dune’s API (with server-side filtering/pagination) or BigQuery’s curated tables for events. Reserve RPC for real-time delta ingestion and confirmations. (docs.dune.com)

Verifiable analytics into smart contracts

If your dApp needs on-chain verification of off-chain analytics, Space and Time’s Proof of SQL can produce sub‑second ZK proofs over million‑row queries and integrate the verified result on-chain via Chainlink. (spaceandtimefdn.github.io)

Chain-specific fast paths to know in 2026

Ethereum and EVM chains
- For historical state, use archive nodes (Infura, Erigon self-hosted). Geth’s archive documentation distinguishes hash-based vs. path-based archives; traces and proofs often require archive data. (docs.metamask.io)
- For proofs/traces at scale, Erigon v3.x reduces storage by multiples and serves proofs/queries with very low latency (p50 milliseconds range in internal benchmarks), making self-hosted archive far more practical. (erigon.tech)
- For real-time, prefer eth_subscribe over polling; always filter logs by address/topics to reduce load and duplicates on reorgs. (docs.metamask.io)
Solana
- Geyser plugins pump accounts and transaction deltas into your own datastore, side-stepping RPC load and enabling millisecond-to-second ingestion. Consider regional RPC endpoints for lower client latency. (docs.solanalabs.com)
Aptos
- Official Indexer GraphQL plus an SDK/processor path means you can stand up fast, typed queries without scraping node REST. Tables are indexed with documented composite keys for efficient filters. (aptos.dev)
Sui
- Sui’s GraphQL Indexer is the recommended high-performance data plane; JSON‑RPC is deprecated by April 2026 in favor of gRPC/GraphQL—plan migrations now. (docs.sui.io)
Data warehouses
- BigQuery has expanded to many chains with Google‑managed Ethereum datasets (curated event tables), but watch for ingestion lags on specific chains (community flagged a Solana pause in Mar–Apr 2025). Use as a complement to real-time streams. (cloud.google.com)

Emerging best practices for fast retrieval in 2026

Parallelize the past, stream the present
- Use Firehose/Substreams or Subsquid’s Archive for backfills and historical sync; use WebSockets (eth_subscribe) or chain-native streams (Geyser, gRPC) for live updates. (thegraph.com)
Avoid wide eth_getLogs scans in production paths
- Enforce short block windows (e.g., ≤3k–10k on busy L2s/L1s), prefilter by address/topics, and paginate. Cache last-processed block per contract to keep incremental windows tiny. (docs.chainstack.com)
Use provider “fast paths” for common needs
- Alchemy’s Transfers API, QuickNode’s Token API, and Covalent’s balances/holders endpoints drastically cut both latency and cost for portfolio features and compliance analytics. (alchemy.com)
Treat traces and historical state as a separate lane
- Route all debug/trace and historical state reads to archive-capable infra (Infura archive, Erigon archive). Keep tight timeouts and backpressure controls to prevent noisy neighbors from hurting user endpoints. (docs.metamask.io)
Co-locate compute and data
- For analytics workloads, push computation to where the data lives (Dune server-side filtering/pagination, BigQuery/ClickHouse materializations). Ship small, filtered result sets to apps. (docs.dune.com)
Plan for chain-specific deprecations and interfaces
- Monitor Sui’s shift to gRPC/GraphQL and Solana’s plugin ecosystem; these materially change how “fast” is achieved for those ecosystems. (docs.sui.io)
Verify when it matters
- For on-chain decisions based on off-chain analytics, adopt verifiable computation like Proof of SQL to make “fast and correct” provable. (spaceandtimefdn.github.io)

Concrete selection guidance: “What blockchain API supports fast data retrieval?”

You need complete historical transfers for an EVM address now
- Choose: Alchemy Transfers API (single call, includes internal and token transfers), or Covalent for multi-chain. You’ll beat any in-house RPC scan by orders of magnitude. (alchemy.com)
You need real-time streaming of on-chain events
- Choose: WebSockets eth_subscribe for EVM; Geyser plugins on Solana; chain-native streams (Aptos Transaction Stream via Indexer processors; Sui GraphQL/gRPC). These avoid the latency and overhead of polling. (docs.metamask.io)
You need a custom index with complex joins/aggregations
- Choose: The Graph Substreams or Subsquid; if you prefer managed, consider Goldsky for subgraphs with performance tuning. For BI, land transformed data in ClickHouse/BigQuery and expose it via a thin API. (thegraph.com)
You need cross-chain analytics or ML features
- Choose: Dune API or BigQuery public datasets for breadth; consider Space and Time if you need verifiable results on-chain. (dune.com)
You need deep historical state/traces for audits
- Choose: Infura archive nodes or a self-hosted Erigon archive for predictable low-latency historical proofs and tracing. (infura.io)

Implementation notes: latency and reliability tricks we deploy at 7Block Labs

Backfills: run parallelized historical jobs (Substreams or Squid) writing to a column store; keep a compact “hot table” in Postgres/ClickHouse for APIs.
Real-time: subscribe to heads/logs; reconcile against finalized blocks; implement idempotent upserts keyed by block number + logIndex to survive reorgs.
RPC hygiene: pin small block windows; use explicit topics/address filters; avoid “earliest..latest”; rotate across multiple providers and regions; retry with exponential backoff and jitter.
Archive lane: route debug/trace calls to a dedicated pool with per-route QPS limits and bulkhead isolation; cache common traces.
Region and protocol: co-locate API gateways with your data store; prefer HTTP/2 or gRPC where supported; for Solana, place Kafka/QUIC listeners in the same AZ as validators or Geyser sources to minimize jitter. (github.com)
Warehouse ergonomics: precompute common aggregates; paginate and server-filter (Dune/BigQuery) to bound payload size; keep SLOs for BI endpoints separate from transactional APIs. (docs.dune.com)

Brief, in‑depth details on critical edge cases

eth_getLogs pitfalls
- Large ranges often timeout or get rate-limited. Use chain-specific range guidance (e.g., 3,000 on Polygon, 5,000 on Ethereum; some providers allow 20,000) and strict topics. Bloom caching on clients like Besu materially improves log retrieval performance. (docs.chainstack.com)
Tracing at scale
- debug/trace endpoints traverse historical state; realistically, you need archive nodes and generous timeouts. If you can’t host one, buy archive access (Infura) or build on Erigon v3.x which reduces storage and raises throughput. (infura.io)
Warehouse freshness
- Public datasets are excellent for analytics but can lag: check last block timestamps programmatically; for mission-critical freshness, pair warehouse with real-time streams into your own delta tables. (discuss.google.dev)
Sui deprecation window
- JSON-RPC deprecates by April 2026; plan GraphQL/gRPC migration to avoid breaking changes and leverage indexer-backed speed. (docs.sui.io)

The bottom line

“What blockchain API supports fast data retrieval?” The fastest answer is rarely a single endpoint. For user-facing products, blend provider pre-indexed APIs (Alchemy, QuickNode, Covalent), with parallel indexers (Substreams/Subsquid/Goldsky) for your custom domain, and use chain-native indexers where available (Aptos/Sui). Reserve direct RPC for real-time streams and small, well-filtered queries, and use warehouses (Dune/BigQuery) for heavy analytics—optionally with verifiable SQL if you need proofs on-chain. Do this, and you’ll hit sub-second to low-seconds SLOs reliably—even at enterprise scale. (alchemy.com)

If you’re evaluating architectures or need a performance bake-off, 7Block Labs can blueprint and stand up the optimal mix—end-to-end—from indexer pipelines to APIs, SLOs, and dashboards.