// SQL Explorer [BETA]

Billions of Onchain Data Records,
Queryable with SQL

Query 500B+ indexed Hyperliquid records. Retrieve results via REST. No pipelines. No additional vendors. All on Quicknode.

Start Building 阅读文档

55M+

Rows Scanned Per Query

500B+

Rows · Hyperliquid

40+

Sample Queries

// why we built this

Trading desks, quant teams, and data engineers all face the same bottleneck.
Reaching indexed onchain data means managing multiple data vendors and maintaining the infrastructure required to expose it.
So we built SQL Explorer.

QUANTTRADINGANALYTICSENGINEERINGDATAINFRASTRUCTURE

// The Product

Meet SQL Explorer

Direct SQL access to indexed Hyperliquid data. Query trades, orders, positions, liquidations, and more. Start from 40+ pre-built queries or write your own, then retrieve results via REST.

Start Building

SQL 资源管理器

▼ Hyperliquid (HyperCore)46 547.4B

▶⊞hyperliquid_agents

1.7B

▶⊞hyperliquid_asset_transfers

11.2M

▶⊞hyperliquid_blocks

307.9M

▶⊞hyperliquid_bridge

245.8M

▶⊞hyperliquid_builder_fills

190.3M

▶⊞hyperliquid_builder_transactions

134.4M

▶⊞hyperliquid_clearinghouse_states

1.5B

▶⊞hyperliquid_delegator_rewards

466.1M

▶⊞hyperliquid_dex_trades

▶⊞hyperliquid_fills

2.6B

▶⊞hyperliquid_funding

1.2B

▶⊞hyperliquid_outcome_markets

▶⊞hyperliquid_outcome_meta

4.7K

▶⊞hyperliquid_outcome_questions

902

▶⊞hyperliquid_outcome_sides

9.4K

▶⊞hyperliquid_perpetual_positions

1.5B

1	SELECT
2	timestamp,
3	coin,
4	side,
5	price,
6	size,
7	price * size AS notional_usd,
8	buyer_address,
9	seller_address,
10	buyer_fee,
11	seller_fee,
12	fee_token
13	FROM hyperliquid_trades
14	WHERE block_time > now() - INTERVAL 1 HOUR
15	ORDER BY block_number DESC, trade_id DESC

CSVJSON100 rows

#	时间戳	硬币	side	价格	大小	notional_usd	buyer_addr
1	2026-03-26 15:27:42.406	AZTEC	A	0.019959	848	16.925232	0x4a6e4878…
2	2026-03-26 15:27:42.406	cash:HOOD	A	70.782	0.707	50.042874	0x9badff1e…
3	2026-03-26 15:27:42.406	cash:HOOD	A	70.782	0.707	50.042874	0xcee1cc9b…
4	2026-03-26 15:27:42.406	ETH	A	2,065.1	2.0458	141.393…	0xb6a766f5…
5	2026-03-26 15:27:42.330	cash:MSFT	A	370.52	0.134	49.64968	0xcee1cc9b…
6	2026-03-26 15:27:42.330	cash:MSFT	A	370.52	0.134	49.64968	0x9badff1e…
7	2026-03-26 15:27:42.330	ARK	A	0.16736	112	18.74432	0x7717a7a2…

Query time: 13msResult rows: 100Rows read: 254.41KBytes read: 9.86 MBEst. credits: 20

// In Action

From Query to REST
In Seconds

SQL Explorer turns any query into a REST endpoint. No ETL, no transformation logic, no additional infrastructure. Just results your systems can consume directly.

// 1

Query Hyperliquid data

SQL Query

-- Hyperliquid liquidation summary: last 24h
SELECT
  count() AS total_liquidations,
  toFloat64(sum(toFloat64(price) * toFloat64(size)))
    AS total_liquidated_volume_usd,
  countDistinct(liquidated_user) AS unique_users_liquidated,
  countDistinct(coin) AS coins_affected,
  countIf(side = 'A') AS long_liquidations,
  countIf(side = 'B') AS short_liquidations
FROM hyperliquid_fills
WHERE is_liquidation = 1
  AND time >= now() - INTERVAL 24 HOUR
  AND user = liquidated_user

// 2

Retrieve results via REST

CURL Example

curl -X POST \
  'https://api.quicknode.com/sql/rest/v1/query' \
  -H 'x-api-key: YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "query": "...",
    "clusterId": "hyperliquid-core-mainnet"
  }'

// 3

Consume structured JSON

JSON Response

{
  "data": [{
    "total_liquidations": 4954,
    "total_liquidated_volume_usd": 28872094.94,
    "unique_users_liquidated": 2013,
    "coins_affected": 76,
    "long_liquidations": 4015,
    "short_liquidations": 939
  }]
}

Start Building 联系销售部

Connect results directly to your trading systems, dashboards, internal workflows, or AI agents.

// See What's Possible

Track the Data That Matters

From validator rewards to trading activity to liquidation events and HIP-4 outcome markets, SQL Explorer gives you direct SQL access to the Hyperliquid data your strategies depend on.

Validator Rewards

Query staking rewards and distribution across validators over any time window. Feed results directly into your dashboards or alert systems.

Trading Activity

Analyze fill history, volume, and execution patterns for any wallet. Ideal for competitive intelligence, strategy validation, or quant research.

清算

Monitor liquidation notional and position sizing across any time range. The input your risk models and market-structure analyses need.

Outcome Markets

Query open questions, side distributions, and settlement data across HIP-4 outcome markets. Track market creation, liquidity, and resolution in real time.

// The Full Suite

One Platform.
Every Data Access Pattern.

SQL Explorer is part of Quicknode's full data suite. Access, stream, and query blockchain data your way, on a unified platform.

Queryable Data

Fully indexed onchain datasets, queryable with SQL and retrievable via REST.

SQL 资源管理器

Data Pipelines

Push-based, deterministic event delivery into your backend systems.

StreamsWebhooks

Raw Blockchain Data

Direct chain access for real-time state reads and transaction submission.

RPCgRPC

// Built Different

How SQL Explorer
Compares

The coverage, performance, and integration your team needs, without the data management overhead.

	SQL Explorer (Beta)	Typical Analytics Platforms
Infrastructure required	None. Runs inside your existing Quicknode account.	Separate vendor and integration work
Query performance	Scans 55M+ rows and GBs per query	Varies, often queue-dependent
Hyperliquid coverage	45+ tables covering protocol activity	Limited or unavailable
API access	REST API for any query result	Often limited or plan-dependent
账单	Metered from your existing Quicknode credit pool	Separate contracts and pricing
Auth and access	Same Quicknode account and API keys	Separate identity systems

Need Data We Don't Have Yet?

SQL Explorer is available on any paid plan today. Enterprise teams can work with us on custom dataset coverage, dedicated capacity, and schema-level support. Tell us what your stack needs.

// FAQ

常见问题解答

The docs cover everything. Our support team is there when you need more.Still have questions? Reach out to support and we'll help you find answers.

What is SQL Explorer?

How is SQL Explorer different from Streams?

How is SQL Explorer different from RPC?

What data is currently available?

How does the REST API work?

How does billing work?

Does SQL Explorer support HIP-4 Outcome Markets?

Is SQL Explorer production ready?

Billions of Onchain Data Records,
Queryable with SQL

Trading desks, quant teams, and data engineers all face the same bottleneck.
Reaching indexed onchain data means managing multiple data vendors and maintaining the infrastructure required to expose it.
So we built SQL Explorer.

Meet SQL Explorer

From Query to REST
In Seconds

Query Hyperliquid data

Retrieve results via REST

Consume structured JSON

Track the Data That Matters

Validator Rewards

Trading Activity

清算

Outcome Markets

One Platform.
Every Data Access Pattern.

Queryable Data

Data Pipelines

Raw Blockchain Data

How SQL Explorer
Compares

Need Data We Don't Have Yet?

常见问题解答

想随时了解最新动态吗？

开发者工具

文档与指南

Billions of Onchain Data Records, Queryable with SQL

Trading desks, quant teams, and data engineers all face the same bottleneck.Reaching indexed onchain data means managing multiple data vendors and maintaining the infrastructure required to expose it.So we built SQL Explorer.

Meet SQL Explorer

From Query to RESTIn Seconds

Query Hyperliquid data

Retrieve results via REST

Consume structured JSON

Track the Data That Matters

Validator Rewards

Trading Activity

清算

Outcome Markets

One Platform.Every Data Access Pattern.

Queryable Data

Data Pipelines

Raw Blockchain Data

How SQL ExplorerCompares

Need Data We Don't Have Yet?

常见问题解答

想随时了解最新动态吗？

开发者工具

文档与指南

Billions of Onchain Data Records,
Queryable with SQL

Trading desks, quant teams, and data engineers all face the same bottleneck.
Reaching indexed onchain data means managing multiple data vendors and maintaining the infrastructure required to expose it.
So we built SQL Explorer.

From Query to REST
In Seconds

One Platform.
Every Data Access Pattern.

How SQL Explorer
Compares