Query the chain · Address labels
Bitcoin address labels and entity attribution API
A raw Bitcoin address is just a string of characters, and on its own it tells you nothing about who controls it. Bitcoin address labels close that gap: BitcoinDatabase clusters addresses that provably share ownership and attaches an informational label where the cluster maps to a known entity, such as a major exchange wallet, a mining pool, a payment processor or a well-known service. Query an address and, alongside its balance and history, you get the label we hold for it.
REST API · SQL · dashboards · address history from genesis
BTC
Balance trail
informational on-chain data · not financial advice
The same labeled data is queryable three ways: the REST API for apps, SQL for analysts who want to join labels against flows, and dashboards for review. It is built for compliance, research and analytics teams who need to read the chain as entities rather than hashes. Labels are informational context from on-chain clustering and public attribution, not identity claims about individuals and not legal or financial advice.
History from genesis queryable in seconds
On-chain data not financial advice
Why it works
What you get with Address labels
Entities, not just hashes
Where an address clusters to a known exchange, miner, pool or service, we attach a label so your query returns an entity name and category, not only a raw string, and your team reads the chain in plain terms.
Clustering you can join
Labels sit next to balances, transactions and fund flows on the same indexed chain, so in SQL you can group flows by entity, filter transactions touching a labeled exchange, or roll up exposure across a cluster in one query.
Informational, not accusatory
Attribution is framed as on-chain context to support your own review, never an identity claim about a person or a guarantee. It surfaces signals; your compliance or research process makes the decisions.
Side by side
We asked nine public Bitcoin APIs to name an address owner
Measured on 6 September 2026 against the live chain at block 965,794, using five addresses chosen for unusually strong public reporting: the most widely reported cold wallet on the chain, a hot wallet with 2,320,473 transactions, the 2010 pizza address, an address on the OFAC SDN list and a large bech32 cold address. Six providers answered without credentials. Exactly one returned a cluster id. Not one returned an entity name.
| Public API | Cluster id | Entity name | What we measured |
|---|---|---|---|
| WalletExplorer | Yes, 5 of 5 | No, label null on all 5 | 200, no key, 135 blocks behind the tip |
| mempool.space | No | No | 200 in 0.11s, no label fields |
| Blockstream Esplora | No | No | 200 in 0.59s, no label fields |
| BlockCypher | No | No | 200 in 0.20s, no label fields |
| blockchain.com | No | No | 200, 8 keys, none about identity |
| Bitquery unauthenticated | No | No | 200, no label fields returned |
| Blockchair | Not testable | Not testable | 430, our IP is blacklisted |
| timechainindex | Key required | Key required | 401, API key required |
| Arkham | Key required | Key required | 400, sign up required |
The split this table exposes is the one that decides your budget. Clustering, which groups addresses that provably co-spend, is arithmetic over the chain and a free API will hand it to you. Attribution, which puts a company name on that cluster, comes from off-chain evidence and nobody gives it away. Two caveats we will state rather than hide: timechainindex and Arkham both refused without keys and may return rich entity data to paying customers, so their rows read key required rather than no, and the Blockchair block is an artifact of our own earlier testing rather than a judgment on their product. One further finding from the same run: two addresses widely reported as cold storage for the same exchange landed in two different WalletExplorer clusters, 011cf39664426f5d and 1c604af8fad4c417. That is not a bug. Common input ownership can only merge addresses that have actually been spent together, and segregated cold storage never co-spends, so any cluster total is a floor rather than a count.
What it handles
The indexed Bitcoin chain, queryable your way
Look up an address, a transaction, a UTXO, the rich list or an on-chain metric, by REST API, SQL or dashboard. The same authoritative data, reconciled block-by-block against the canonical chain, without running a node.
- Return exchange, miner, pool and service labels
- Group fund flows by labeled entity in SQL
- Filter transactions touching known clusters
- Enrich address lookups with attribution context
- Label a whole address list in one query, not one call per address
- Join labels to balances and flows without a second dataset
- Feed labeled data into AML and research workflows
GET /v1/address/{addr}
query result
{
"address": "bc1qxy2k…l0wdv8",
"balance_btc": 68432.10,
"balance_usd": 4612165420,
"tx_count": 1284,
"unspent_outputs": 37,
"first_seen": "2014-02-09"
}
Why BitcoinDatabase
One platform, queryable three ways
Not a raw node to sync, not an indexer to build, and not five vendors to stitch together. The fully-indexed Bitcoin blockchain, available as a REST API, as SQL, and as dashboards, on one authoritative dataset.
REST API
Typed JSON for addresses, transactions, balances, UTXOs and metrics. Drop it into apps, wallets, explorers and agents with curl, Python or any HTTP client.
SQL access
Run SQL directly against the indexed Bitcoin dataset for ad-hoc analysis, cohorts and exports, the same data the API and dashboards read from.
Compliance-first
Informational on-chain data and analytics only. Entity labels and flow tracing are framed as tooling to support a regulated team's own review, not accusations.
Good questions
Questions about Address labels
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Stop running a node. Just query Bitcoin.
Run your first query now and get on-chain data back by REST API, SQL or dashboard, with address history back to the genesis block over REST. Informational on-chain data only, not financial advice.
History from genesis over REST · SQL · dashboards · addresses, transactions, UTXOs, metrics