We extract network activity, exchange flows, SOPR, and derivatives data from Glassnode. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Network Activity objects from glassnode.com. All fields typed and schema-versioned.
"asset": "BTC", "date": "2026-05-12T00:00:00Z", "active_addresses": 942105, "new_addresses": 412590, "transaction_count": 315420, "transfer_volume": 45210.5, "fees_total": 24.5, "fees_mean": 7.7e-05
| # | asset | date | active_addresses | new_addresses | transaction_count | transfer_volume |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Exchange Flows objects from glassnode.com. All fields typed and schema-versioned.
"asset": "ETH", "exchange": "Binance", "inflow_volume": 145000.2, "outflow_volume": 121000.5, "net_flow": 23999.7, "exchange_balance": 4500120.4, "percentage_of_supply": 3.75, "date": "2026-05-12T00:00:00Z"
| # | asset | exchange | inflow_volume | outflow_volume | net_flow | exchange_balance |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Miner Metrics objects from glassnode.com. All fields typed and schema-versioned.
"asset": "BTC", "miner_balance": 1820450.5, "miner_revenue": 450.2, "difficulty": 83500000000000, "hashrate": 612000000, "puell_multiple": 1.15, "thermocap": 54200000000, "date": "2026-05-12T00:00:00Z"
| # | asset | miner_balance | miner_revenue | difficulty | hashrate | puell_multiple |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Market Indicators objects from glassnode.com. All fields typed and schema-versioned.
"asset": "BTC", "price": 64210.5, "market_cap": 1260000000000, "realised_cap": 485000000000, "mvrv_z_score": 2.14, "sopr": 1.02, "nvt_signal": 45.2, "date": "2026-05-12T00:00:00Z"
| # | asset | price | market_cap | realised_cap | mvrv_z_score | sopr |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Derivatives objects from glassnode.com. All fields typed and schema-versioned.
"asset": "BTC", "exchange": "Deribit", "open_interest": 45000.5, "funding_rate": 0.012, "liquidations_long": 1200000.0, "liquidations_short": 450000.0, "volume": 850000000.0, "date": "2026-05-12T00:00:00Z"
| # | asset | exchange | open_interest | funding_rate | liquidations_long | liquidations_short |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Glassnode relies on heavy React applications and complex chart rendering logic to display data. Our pipeline intercepts the raw underlying data streams before they reach the browser, providing pure, structured time-series data.
Extract active addresses, transaction counts, transfer volumes, and fee metrics across Bitcoin, Ethereum, and major ERC-20 tokens.
Capture inflow, outflow, net flow, and total exchange balance data segmented by individual exchanges or aggregated.
Track miner balances, revenue streams, Puell Multiple, difficulty adjustments, and hashrate distributions in real time.
Extract complex derived metrics like MVRV Z-Score, SOPR (Spent Output Profit Ratio), Realised Cap, and NVT Signal.
Monitor open interest, perpetual funding rates, futures volume, and liquidation cascades across major derivatives platforms.
Access Glassnode's proprietary entity-adjusted data, filtering out internal exchange transfers and change addresses for cleaner signals.
Extract complete historical time-series data for any supported metric, allowing you to build and test quantitative models from genesis blocks.
Capture high-frequency block-by-block data where available, bypassing the standard daily or hourly aggregation views.
Run continuous pipelines that append new metric points as they are published, maintaining an up-to-date data warehouse without manual exports.
Brief in. Clean data out.
Specify the assets (BTC, ETH, DeFi tokens), metrics (SOPR, Flows), and resolution (daily, hourly, block) required.
We configure Playwright interceptors to bypass Cloudflare and extract the raw JSON payloads powering Glassnode's charts.
We validate data continuity, precision matching, and handle timezone normalisation against the raw blockchain state.
Structured time-series data pushed via Parquet or JSON to your S3, BigQuery, or Snowflake instances.
Extracting data from financial intelligence platforms requires intercepting backend APIs rather than parsing HTML. Here is how we ensure data integrity.
Glassnode displays data using complex HTML5 Canvas and SVG charts which are impossible to scrape via DOM parsing. We use Playwright to intercept the underlying XHR/Fetch requests, extracting the raw JSON time-series data before it hits the charting library.
Financial data platforms employ strict Cloudflare protection. Our infrastructure utilises TLS fingerprint spoofing, residential proxies, and automated CapSolver integration to maintain uninterrupted access to the public data endpoints.
Long-term historical charts often load data in chunks based on the zoom level. Our crawlers programmatically manipulate the date range parameters to extract the complete, unaggregated dataset from genesis to present.
We normalise all Unix timestamps to UTC ISO-8601 strings and preserve the exact floating-point precision of the original metrics, ensuring your quantitative models receive mathematically accurate inputs.
Instead of redownloading the entire history every day, our pipelines track the latest timestamp per metric and only extract the delta, optimising pipeline execution time and reducing your storage costs.
Algorithmic funds ingest SOPR, NVT, and funding rates to build mean-reversion and momentum models for digital assets.
Research desks track exchange balances and miner accumulation phases to gauge market cycle positioning and liquidity.
Lending protocols and OTC desks monitor derivative liquidations and open interest to adjust collateral requirements dynamically.
Asset managers aggregate on-chain activity metrics to provide institutional clients with fundamental valuation reports.
Protocol treasuries track capital flows across Ethereum and Layer 2s to optimise yield strategies and liquidity provision.
Universities and economic institutes extract historical entity-adjusted data to study market efficiency and network effects.
"On-chain metrics provide the fundamental valuation layer for digital assets, but extracting structured time-series data from charting UIs requires dedicated interception infrastructure."
Attempting to scrape Glassnode via traditional DOM parsing fails immediately due to Canvas rendering and Cloudflare protections. DataFlirt intercepts the raw API traffic, handles the pagination of historical data, and delivers clean, mathematically precise time-series arrays directly to your quantitative infrastructure. We handle the extraction so your quants can focus on alpha.
Everything supported by our glassnode.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Playwright handles the headless browser execution, specifically configured to intercept and dump XHR/Fetch responses containing the raw time-series data before Canvas rendering.
We utilise ISP-grade residential proxies to distribute requests and avoid rate-limiting or IP bans from Glassnode's Web Application Firewall (WAF).
Apache Airflow manages the scheduling and dependency logic, ensuring that daily or hourly metric updates are fetched, validated, and pushed to your warehouse reliably.
Data delivered to where your team already works — no new tooling required.
About glassnode.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly accessible, unauthenticated data from Glassnode is generally permissible. DataFlirt extracts only the data that is freely visible on the public frontend. We do not bypass authentication to access paid Tier 2 or Tier 3 metrics. Clients should consult their legal counsel regarding their specific use cases and Glassnode's Terms of Service.
We do not use OCR or DOM parsing on the visual charts. Instead, our infrastructure intercepts the background network requests (XHR/Fetch) that the frontend application makes to Glassnode's backend servers, capturing the raw JSON arrays containing the exact timestamps and metric values.
Yes. Our pipelines can manipulate the date parameters in the intercepted requests to paginate backwards, extracting the complete historical dataset for any public metric from the asset's genesis block to the present day.
Depending on the specific metric's publication schedule, we can configure pipelines to run daily, hourly, or at sub-minute intervals to capture the latest data points as soon as they are pushed to the frontend.
No. DataFlirt focuses exclusively on extracting publicly available data. We do not manage authenticated sessions or extract data that requires a paid Glassnode subscription.
For quantitative backtesting, we recommend Parquet or CSV. Parquet is highly efficient for large historical datasets loaded into pandas or polars, while CSV offers immediate readability and compatibility with standard financial modelling tools.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete historical backfill of Bitcoin metrics or a continuous feed of Ethereum exchange flows — we build and operate the infrastructure. Tell us what you need.
