Onchain Analytics Platforms for Crypto Teams (2026)

Every significant crypto event of the past two years was visible onchain before it hit the news.

The German government selling 50,000 BTC. The FTX hacker moving $477 million. UST's Curve pools draining hours before the depeg. Mt. Gox finally distributing to creditors. In each case, someone watching the right dashboard knew first.

Onchain data has shifted from a nice-to-have for researchers to operational infrastructure for any serious crypto team. Protocol teams use it to understand user behavior and automate workflows. Investors use it to validate narratives and track smart money. Security teams use it to detect exploits in real-time.

But the tooling landscape is fragmented. Each platform takes a different approach to the same underlying data—and choosing the wrong one means either building dashboards that already exist elsewhere or missing signals that could cost millions.

This guide covers the four platforms that matter most for professional crypto teams in 2026:

• Dune: The community-driven query platform where anyone can analyze raw onchain data across 100+ chains
• Nansen: The smart money intelligence layer with 500M+ labeled addresses and real-time alerts
• Arkham: The blockchain investigation platform with an AI-powered entity identification engine
• Token Terminal: The financial metrics standard, bringing income statements and balance sheets to protocols

These aren't interchangeable products. They solve different problems for different users. A trading firm's stack looks nothing like a protocol team's. The goal here is to help you understand what each platform actually does well—and where it falls short—so you can build the right analytics stack for your needs.

Dune

Dune is where most onchain analysis happens. It's a community-driven platform that lets anyone query blockchain data using SQL, build visualizations, and share dashboards publicly. If you've seen an onchain chart on Twitter, there's a good chance it came from Dune.

The core proposition is simple: raw blockchain data is messy and hard to access. Dune indexes it, decodes smart contract interactions, and makes it queryable through a web-based SQL editor. No infrastructure to manage. No RPC nodes to run. Just write a query and get results.

Key Features

• Query any onchain data: Dune supports 100+ chains—every major EVM network, Solana, Bitcoin, and more. Data is indexed and available through a unified query interface. Want to compare DEX volumes across Ethereum, Arbitrum, and Base? One query.
• 60,000+ decoded contracts: Smart contract data is notoriously hard to parse. Dune automatically decodes contract ABIs, turning raw transaction logs into human-readable tables. Instead of parsing hex data, you query uniswap_v3.swaps directly.
• Materialized views and scheduling: For teams that need production-grade data pipelines, Dune supports materialized views that refresh on a schedule. Build a dashboard once, and it stays current without manual intervention.
• AI query generation: Dune's AI tools let you describe what you want in natural language and generate SQL. Useful for non-technical team members or for speeding up exploratory analysis. The generated queries are editable, so you can refine them.
• Data upload: Bring your own data into Dune and join it with onchain data. CoW Protocol uses this to combine internal database records with onchain transactions for solver reward calculations—a workflow that would be painful to build from scratch.
• Community dashboards: This is Dune's moat. Thousands of analysts have published dashboards covering nearly every protocol, token, and trend. Before building something custom, search Dune—someone has probably already done the work.

Best For

• Protocol teams building transparency dashboards and tracking KPIs
• Analysts doing custom research that requires flexible queries
• Investors who want to verify claims with primary data
• Anyone who needs a specific analysis that doesn't exist elsewhere

Real-World Example: CoW Protocol

CoW Protocol, a DEX aggregator, uses Dune as core infrastructure for both analytics and operations.

User analytics. They built dashboards tracking active users by segment, retention rates, and lifetime value. The entire team reviews a monthly report dashboard together to understand performance and plan strategy.

Automated payments. CoW's solver reward system runs on Dune. They upload internal data, join it with onchain settlement data, calculate rewards, and export the results for distribution. This happens weekly, automatically.

Fraud detection. Solvers in CoW's system could theoretically game the protocol. Dune queries power an alert system that monitors for suspicious behavior and pings Slack when thresholds are breached.

The key insight. Dune isn't just for charts. It's programmable infrastructure that protocol teams can build workflows on top of.

The free tier is genuinely useful. Most individual analysts never need to upgrade. Teams typically need Plus or Pro for private dashboards and faster query execution.

Limitations

• Requires SQL knowledge: The AI tools help, but serious analysis still requires understanding how to write and debug queries. Non-technical users will hit a wall.
• No pre-built smart money labels: Unlike Nansen, Dune doesn't tell you which wallets belong to funds, whales, or known entities. You're working with raw addresses unless the community has labeled them.
• Query performance varies: Complex queries on large datasets can be slow, especially on the free tier. Production dashboards need careful optimization.
• Data freshness: Dune isn't real-time. Depending on the chain, data can lag by minutes to hours. Not suitable for time-sensitive trading signals.

Nansen

Nansen's core insight is that not all wallets are equal. Some addresses belong to top-performing funds, early token accumulators, or known smart money operators. If you can identify and track those wallets, you can see where capital is flowing before it shows up in price.

The platform has indexed and labeled over 500 million addresses—tagging them by entity type, historical performance, and behavior patterns. This labeling layer sits on top of raw blockchain data and turns anonymous addresses into actionable intelligence.

Key Features

• 500M+ labeled addresses: This is Nansen's moat. Years of work identifying which wallets belong to funds, exchanges, whales, smart money operators, and specific entities. When a wallet moves, you don't just see an address—you see "Paradigm" or "Smart Money Early Accumulator" or "CEX Hot Wallet."
• Smart Alerts: Set conditions and get notified when they trigger. Track when a specific wallet moves tokens, when smart money accumulates a position, or when liquidity pools see unusual outflows. Alerts go to email, Telegram, or Slack.
• Token God Mode: Deep analysis for any token: who holds it, how concentrated ownership is, what smart money is doing, recent large transactions, and DEX trading patterns. The standard starting point for token due diligence.
• Nansen AI: A conversational interface for onchain research. Ask questions in natural language—"What are the top wallets accumulating ETH this week?"—and get answers pulled from Nansen's data. The mobile app leans heavily on this for quick research on the go.
• In-app trading: Spot a signal, execute a trade, without leaving Nansen. The platform is evolving from pure analytics toward an integrated research-to-execution workflow.
• Smart Segments: Create custom wallet groups based on criteria you define. Track a basket of addresses as a cohort—useful for monitoring competitor protocols, investor behavior, or your own power users.

Best For

• Traders looking for smart money signals and early accumulation patterns
• Funds doing due diligence on token holdings and whale concentration
• Protocol teams tracking how specific investor cohorts interact with their product
• Anyone who needs real-time alerts on wallet movements

Real-World Example: Valkyrie and the UST Depeg

In May 2022, Valkyrie's team had Nansen alerts configured to monitor Curve pool balances. When UST's pools started draining—hours before the depeg made headlines—the alerts fired.

The team exited their positions early. In their words: "Nansen's Smart Alerts helped us detect early that the UST Curve pools were getting drained. As a result, we saved tens of millions of dollars by being able to exit early."

This is Nansen's value proposition in a sentence: see what's happening before the market prices it in.

Pricing

Nansen doesn't publish pricing publicly. The platform operates on a subscription model with tiered access:

Expect to pay in the low hundreds per month for meaningful access. Enterprise deals are negotiated. The free tier exists but is heavily limited—it's a trial, not a product.

Limitations

• Proprietary labels, opaque methodology: Nansen doesn't fully explain how they identify and categorize wallets. You're trusting their classification. When they label something "Smart Money," you can't independently verify the criteria.
• Trading-focused: The product is optimized for identifying short-to-medium term signals. Less useful for protocol teams doing operational analytics or long-term research.
• Price: Nansen is expensive relative to free alternatives like Dune. The value is in the labeling layer—if you don't need smart money tracking, you're paying for something you won't use.
• Signal vs. noise: 500M labels sounds impressive, but most wallets aren't interesting. The challenge is filtering down to the signals that actually matter for your strategy. Takes time to configure alerts that aren't spammy.
• Less flexibility than Dune: You're working with Nansen's pre-built views and dashboards. Custom queries and novel analysis require their team's help or aren't possible at all.

Arkham

Arkham takes a different approach than the other platforms on this list. Where Dune gives you query tools and Nansen gives you labeled dashboards, Arkham is built for investigation—tracing funds, identifying entities, and following money across chains.

The platform combines an AI-powered identification engine (called Ultra) with a marketplace where analysts can buy and sell intelligence. It's part analytics tool, part bounty platform, part investigative infrastructure.

Key Features

• AI-powered entity identification: Arkham's Ultra engine analyzes onchain behavior patterns to identify wallet owners. It cross-references transaction timing, interaction patterns, and known entity behaviors to make educated guesses about who controls an address. The result: 350 million labels across 200,000+ entity pages.
• Entity pages: Each identified entity gets a dedicated page showing all associated wallets, transaction history, portfolio holdings, balance changes over time, P&L, and exchange usage. Search "German Government" and you get a complete view of their BTC holdings and movements.
• Visualizer: Trace fund flows visually. Select a transaction or wallet and see where money came from and where it went, rendered as an interactive graph. Essential for following complex transaction chains—the kind that appear in hacks, exploits, or suspicious activity.
• Multi-chain coverage: Bitcoin, Ethereum, Tron, BNB Chain, Polygon, Arbitrum, and more. Cross-chain tracing is where Arkham shines—following funds that hop between networks to obscure their origin.
• Intel Exchange: This is Arkham's novel contribution: a marketplace for blockchain intelligence. Anyone can post a bounty ("Identify the wallet behind this hack") and analysts compete to solve it. Payouts happen through smart contracts. You can also auction intelligence you've gathered.
  
  The Intel Exchange creates an economic incentive for onchain investigation. Instead of doing research for free or keeping it private, analysts can monetize their work.

Best For

• Security teams investigating hacks, exploits, or suspicious activity
• Compliance and legal teams doing due diligence or supporting litigation
• Journalists and researchers tracking fund flows for stories
• Funds evaluating counterparty risk or verifying claims about wallet ownership
• Onchain analysts who want to monetize their investigation skills

Real-World Examples

FTX collapse (November 2022). When $477 million moved out of FTX during the bankruptcy, Arkham tracked the hacker in real-time. Their analysts identified behavioral patterns: the attacker operated between 08:00-10:00 UTC and created new wallets for each operation. They also tracked $1.7 million in fund movements tied to Sam Bankman-Fried himself. This data was later used by prosecutors in the Southern District of New York.

German government BTC sales (July 2024). When Germany's Federal Criminal Police Office started liquidating 50,000 BTC seized from Movie2k operators, Arkham had already tagged the wallets. Users watched in real-time as billions in Bitcoin moved to Coinbase, Kraken, and Bitstamp over several weeks.

Mt. Gox repayments (2024). Arkham tagged Mt. Gox trustee wallets holding 140,000 BTC. When repayments to creditors finally began—a decade after the exchange collapsed—the crypto world tracked every movement through Arkham's dashboards.

Celsius bankruptcy (2022). During Celsius's collapse, Arkham identified that the company owed over $500 million to Aave, Compound, and other DeFi lenders—information that wasn't publicly disclosed at the time.

Pricing

The free tier is surprisingly functional for basic research. Pro unlocks the full investigation toolkit. The Intel Exchange operates on the ARKM token—you stake tokens to post bounties, and analysts earn tokens for solving them. Paying with ARKM gets up to 60% discounts on platform fees.

Limitations

• The "doxxing" debate: Arkham's entire value proposition is identifying who controls wallets. Some in crypto see this as legitimate transparency; others see it as a surveillance tool that undermines privacy. The platform has drawn criticism for enabling anyone to put a bounty on identifying wallet owners—including potentially malicious actors.
• Investigative focus, not operational: Arkham is built for answering "who did this?" and "where did the money go?"—not for building dashboards or tracking protocol metrics. If you need ongoing analytics rather than investigation, look elsewhere.
• Label accuracy varies: AI-powered identification is probabilistic. Arkham's labels are educated guesses, not verified facts. High-confidence identifications (exchanges, known funds) are reliable. Edge cases and smaller entities may be wrong.
• Intel Exchange is niche: The marketplace is interesting but thin. Most users won't post or solve bounties—it's a power-user feature for dedicated investigators.
• Entity pages can lag: New wallets and recent activity may not be immediately reflected. The platform prioritizes depth over real-time coverage.

Token Terminal

Token Terminal asks a simple question: what if you could analyze protocols the way you analyze companies?

Traditional finance has standardized metrics—revenue, expenses, P/E ratios, margins. Crypto has... TVL, maybe. Token Terminal is building the accounting standards for onchain protocols, translating raw blockchain data into financial statements that institutional investors actually know how to read.

The platform doesn't give you raw query access or wallet labels. Instead, it gives you curated, standardized metrics: fees, revenue, expenses, active users, and more—calculated consistently across hundreds of protocols and chains.

Key Features

• Financial statements for protocols: Token Terminal presents protocol data in familiar formats: income statements showing fees, revenue, and expenses over time. This isn't just labeling—the platform makes opinionated decisions about what counts as revenue vs. supply-side fees, how to categorize expenses (token emissions), and how to calculate margins.
  
  For example, Ethereum's income statement shows monthly fees, what portion goes to validators (supply-side), what remains as protocol revenue, and token issuance as an expense. You can compare it directly to Solana or Arbitrum using the same framework.
• Standardized metrics across protocols: The value is in consistency. "Daily active users" means the same thing whether you're looking at Uniswap or Aave. "Fees" are calculated the same way for every DEX. This lets you make apples-to-apples comparisons that would take hours to construct manually.
• Multi-chain coverage: Fees, users, volume, and TVL across all major chains.
• Bloomberg Terminal integration: Token Terminal is available on the Bloomberg Terminal App Portal. This signals who the target user is.
• API and data infrastructure: For teams that need programmatic access:
  • Sheets integration for analysts who live in spreadsheets
  • API for data scientists building models
  • Data Room for technical teams that need raw data pipelines

Best For

• Institutional investors doing fundamental analysis and valuation
• Research analysts who need standardized metrics for reports
• Protocol teams benchmarking against competitors
• Anyone who thinks in P/E ratios and wants to apply that lens to crypto

Pricing

The free Explorer tier provides access to dashboards and basic metrics. Paid tiers unlock export capabilities, API access, and raw data. Enterprise pricing for Data Room is negotiated.

Limitations

Opinionated metrics. Token Terminal makes decisions about what counts as revenue, how to handle token emissions, and which fees matter. These choices are reasonable but debatable. If you disagree with their methodology, you can't easily change it.

Less raw data access. This isn't a query platform. You can't write custom SQL or explore arbitrary onchain data. You get Token Terminal's curated views, not the underlying tables.

Metrics-focused, not investigation. No wallet tracking, no smart money labels, no entity identification. Token Terminal answers "how is this protocol performing?" not "who is using it?" or "where did these funds come from?"

Coverage gaps. Not every protocol is indexed. Newer or smaller projects may not have data. The platform prioritizes depth on major protocols over breadth across the long tail.

Traditional finance lens has limits. Some crypto-native dynamics don't map cleanly to income statements. Token emissions as "expenses" is a reasonable convention, but it's not how most crypto participants think about tokenomics. The TradFi framing is a feature for institutional users and a limitation for crypto-native analysis.

Which Platform for Which Job?

Skip the analysis—here's what to use for common tasks.

By Use Case

"I need to build a public dashboard for my protocol"
→ Dune. Community expects it, embeds work everywhere, free tier is sufficient.

"I want to track what smart money is buying"
→ Nansen. This is their entire product. 500M labeled addresses, pre-built smart money segments.

"Someone hacked us and we need to trace the funds"
→ Arkham. Visualizer for fund flows, cross-chain tracing, entity identification. Post a bounty on Intel Exchange if you need help.

"I need to compare protocol fundamentals for an investment memo"
→ Token Terminal. Standardized metrics, income statements, apples-to-apples comparisons.

"I want real-time alerts when a specific wallet moves"
→ Nansen or Arkham. Both offer wallet alerts. Nansen better for trading signals, Arkham better for investigative monitoring.

"I need to automate a workflow with onchain data"
→ Dune. Materialized views, scheduling, data upload. CoW Protocol runs their entire solver rewards system on it.

"I want to verify a project's claimed metrics"
→ Dune for raw data verification. Token Terminal if you want pre-calculated metrics to sanity-check against.

"I need data for a Bloomberg Terminal workflow"
→ Token Terminal. Literally integrated into Bloomberg. Run APPS TOKEN GO.

"I want to understand who's behind a wallet"
→ Arkham for investigation and entity identification. Nansen if you just need to know if it's smart money.

"I need to export data to a spreadsheet"
→ Token Terminal (Sheets integration) or Dune (CSV export on paid tiers).

"I'm non-technical and can't write SQL"
→ Token Terminal or Nansen. Both offer pre-built dashboards. Dune's AI helps but still assumes some technical comfort.

By Team Type

Protocol team (building a product)

Trading firm / Fund

VC / Research analyst

Security / Compliance team

Conclusion

No single platform does everything. That's the main takeaway.

Dune is the open layer—flexible, community-driven, free to start. If you can write SQL (or prompt an AI to write it for you), you can analyze almost anything. Best for protocol teams and analysts who need custom views.

Nansen is the smart money layer—500M labeled addresses, real-time alerts, trading signals. Best for funds and traders who need to know what whales are doing before everyone else does.

Arkham is the investigation layer—entity identification, fund tracing, bounty marketplace. Best for security teams, compliance, and anyone who needs to answer "who's behind this wallet?"

Token Terminal is the institutional layer—standardized financials, Bloomberg integration, apples-to-apples comparisons. Best for investors who think in income statements and VCs writing investment memos.

The Minimum Stack

If you're just getting started:

1. Dune (free) for custom queries and exploring community dashboards
2. Token Terminal (free tier) for quick protocol comparisons

Add Nansen when you need smart money tracking. Add Arkham when something goes wrong and you need to trace funds.

The Broader Point

Onchain data used to be a research curiosity—something for crypto-native analysts to play with. That era is over.

Today, protocol teams run production workflows on Dune. Funds make allocation decisions based on Nansen alerts. Prosecutors build cases using Arkham data. Institutions pull Token Terminal into Bloomberg.

The underlying blockchain data is public and permissionless. But the tools to make sense of it—to query, label, standardize, and act on it—are now critical infrastructure.

The teams that figure out how to use this infrastructure well have an edge. Everyone else is trading blind.