> ## Content Index > Fetch the complete content index at: https://stablecoininsider.org/llms.txt > Use this file to discover other available public pages before exploring further. # Best Stablecoin Data and Analytics Platforms - URL: https://stablecoininsider.org/best-stablecoin-data-analytics-platforms/ - Published: 2026-10-30T10:20:46.000Z - Updated: 2026-10-30T10:20:46.000Z - Description: Six platforms compared on where the number comes from and whether you can audit it. Filtering, published methodology, delivery and the sources that share one dataset. - Author: Milos Djukanovic - Tags: Analysis, Stablecoins Two reputable platforms can report the same month of stablecoin activity and differ by a factor of five. Neither is lying, and that is the problem. Nearly all of the headline numbers in this industry are filtered numbers, and the filter is where the judgement lives. Visa's adjusted figure removed roughly 79 percent of raw volume, and Allium's 2026 report puts adjusted volume at about 17.6 percent of raw. So this compares six platforms on where the number comes from, whether the methodology is published, and whether you can reproduce it yourself. > Raw volume is not a more honest number than adjusted volume. It is a different number, mostly describing automated programs rather than payments, and quoting either one without naming the filter is the actual error. ### Key Takeaways - Adjusted stablecoin volume is roughly one fifth of raw volume. - Visa grew its labelled address set from 15 to 600 million. - Messari states it sources stablecoin data from Token Terminal. - Only DefiLlama publishes adapters anyone can inspect and contribute to. - Ask which filter produced a number before you quote it. --- ## Why Two Platforms Report Different Volumes Three decisions sit between a blockchain and a chart, and each platform makes them differently. The first is labelling, meaning which addresses are classified as exchanges, bots, bridges, contracts or infrastructure. The second is exclusion, meaning which of those labelled flows get removed before the total is published. The third is attribution, meaning which chain or participant a transfer is credited to. Our own analysis of [**USDT versus USDC volume**](https://stablecoininsider.org/usdt-is-2-5x-bigger-than-usdc-and-moves-3x-less/) runs into exactly this, noting that Artemis produces a much higher estimate than Visa on the same chains. **What to note:** a volume figure without a stated filter is not a data point, it is a claim. [![USDT Is 2.5x Bigger Than USDC and Moves 3x Less](https://storage.ghost.io/c/73/6a/736af0e4-2274-4543-a329-2952b2b52abc/content/images/2026/10/Screenshot-2026-10-30-at-11.16.14.png)](https://stablecoininsider.org/usdt-is-2-5x-bigger-than-usdc-and-moves-3x-less/) --- ## Best Stablecoin Data and Analytics Platforms ### 1\. [Allium](https://www.allium.so/product/allium-terminal) [](https://www.allium.so/product/allium-terminal) **Does the job:** the substrate under several numbers you have already quoted. Allium is the enterprise layer behind a surprising share of published stablecoin research, which makes understanding its adjustments more useful than understanding most dashboards. The platform supports: - Stablecoins, tokenised assets and prediction markets across more than 10,000 protocols - A stated measurement of more than 200 billion dollars of daily stablecoin volume - Use-case splits for B2B, B2C, C2B and C2C per chain, with sender and receiver geography - The volume adjustment used by Visa Onchain Analytics, plus bot, protocol-mechanic and routing removal - Delivery by dashboard, warehouse datashare to Snowflake, BigQuery, Databricks, S3 or GCS, APIs at 50 to 100 milliseconds across 20-plus chains, and event streams - SOC 1 and SOC 2 Type I and II certification, with Circle, Paxos, Visa, MAS and BCG named Custom SQL is a separate product rather than part of Terminal, no pricing is published, and the accuracy claim of being within 0.000011 percent of node data measures indexing fidelity rather than whether the adjustments are correct. Best for institutions that need the underlying data in their own warehouse, with an audit trail. ### 2\. [Visa Onchain Analytics](https://corporate.visa.com/en/sites/visa-perspectives/trends-insights/making-sense-of-stablecoins.html) [](https://corporate.visa.com/en/sites/visa-perspectives/trends-insights/making-sense-of-stablecoins.html) **Does the job:** the free public reference point, and the most cited one. Visa built the dashboard with Allium in 2024 and it has become the default citation for stablecoin volume, which is reason enough to understand how its adjusted figure is produced. The platform supports: - Free public access to aggregated stablecoin data, with no account required - Active users, volumes by coin and by chain, and transaction size distributions - An adjusted volume view removing what Visa calls inorganic data - A published contrast between adjusted and unadjusted totals - A changelog documenting methodology revisions The exclusion rules are described as a simple heuristic rather than specified, and the September refresh expanded the labelled address set from about 15 million to roughly 600 million, which lowered adjusted volume while the adjusted transaction count fell by under 2 percent. Visa's own methodology page still cites over 3 million labelled addresses, so the documentation and the changelog disagree. Best for public citation and trend reading, provided you note the methodology version you used, and our summary of the [**Allium stablecoins report**](https://stablecoininsider.org/allium-stablecoins-report-2026/) shows what the adjusted view produces over a full year. ### 3\. [Artemis](https://www.artemisanalytics.com/products/data-share) [](https://www.artemisanalytics.com/products/data-share) **Does the job:** the counterweight, with a looser filter and a geography focus. Artemis matters in this comparison precisely because it disagrees with Visa on the same chains, which makes it the obvious second source. The platform supports: - Stablecoin and digital asset tables delivered inside Snowflake - Pre-joined ez\_metrics tables, reducing the work of combining sources - Geographic location of stablecoin users and the types of onchain activity they perform - Where stablecoins are moving between ecosystems, alongside TVL, capital and user flows - Deeper fundamentals such as fees generated by pool Snowflake is the named delivery destination, which rules it out for teams without that warehouse. The data share page also names no chains, does not state whether methodology is published, and does not publish pricing, so the basis of its higher volume estimate has to be asked for. Best for teams on Snowflake who want a second estimate to sanity check the first. ### 4\. [Token Terminal](https://tokenterminal.com/docs/catalog/stablecoins/metrics) [](https://tokenterminal.com/docs/catalog/stablecoins/metrics) **Does the job:** defines each metric precisely, which is rarer than it sounds. Token Terminal is the most disciplined entry on definitions, publishing what each measure means at three levels of granularity rather than offering one blended number. The platform supports: - Daily figures per stablecoin, per stablecoin and chain, and per deployment - Supply split into native, bridged and an off-chain component representing unrepresented NAV - Usage as app TVL, trading volume, transfer count and volume, and daily, weekly and monthly actives - Issuance as mints, redemptions and holders - Price in USD plus an off\_peg deviation expressed as a decimal fraction - Table-level definitions, including what counts as every representation of an asset Two caveats that change interpretation. Holders are summed across deployments, so one address active on two chains counts twice, and stablecoins priced from the peg rate itself have an off\_peg of zero by construction rather than by observation. No methodology document is linked from the metrics page, and access runs through a SQL catalog with compute billed to your own cloud project. Best for analysts who need the definition to be unambiguous before the number matters. ### 5\. [Dune](https://docs.dune.com/api) [](https://docs.dune.com/api) **Does the job:** you write the filter, which is the point. Dune is the only entry here where the methodology is yours, because you query decoded chain data directly in SQL rather than consuming someone's aggregate. The platform supports: - A SQL query engine over a data catalog of decoded onchain data - Public queries, so another analyst's filter can be read and forked - API access for automated extraction into your own workflow - Datashare Enterprise for organisations needing guaranteed freshness and support - Warehouse publishing of dbt-managed transformation outputs The documentation is thin where it matters for procurement. The API page does not state which data is available, rate limits, credits or whether a free tier exists, and the Datashare page promises guaranteed delivery times under an SLA without naming a single timeframe, lists no datasets and no destinations beyond a warehouse. Best for teams who would rather own the filter than inherit one, and have the SQL capacity to do it. ### 6\. [DefiLlama](https://docs.llama.fi) [](https://docs.llama.fi) **Does the job:** the only fully inspectable methodology in the group. DefiLlama is free and open source, and every metric has an adapter repository anyone can read, which makes it the most auditable option here by a wide margin. The platform supports: - Open-source adapter repositories per metric, open to contribution - Stablecoin circulating supply and peg tracking through a dedicated repository - Documented exclusions, such as uncirculated and unvested tokens - Single counting within a protocol, so redeposited receipt tokens are not double counted - Chain attribution based on where users deposited and interacted - Published decisions on contested cases, including bridges, native staking and liquid staking The trade-offs are real. Most pricing comes from a third-party API rather than from the chain, the licence is not stated on the methodology page, that page does not mention an API or whether one is free, and the stablecoin calculation itself is described only by pointing at a repository. Best for anyone who needs to show their working, and for research that has to survive a methodology challenge. --- ## Compared | Platform | Filter | Methodology inspectable | Delivery | Pricing published | | ---------------------- | ------------------------------------ | ------------------------------------- | ---------------------------------- | ------------------- | | Allium | Its own adjustment, used by Visa | Described, not reproducible | Dashboard, warehouse, API, streams | No | | Visa Onchain Analytics | Adjusted, Allium-powered | Heuristic stated, rules not specified | Free public dashboard | Free | | Artemis | Looser, produces higher volumes | Not stated on the data share page | Snowflake data share | No | | Token Terminal | Defined per metric, not adjusted | Definitions yes, methodology doc no | SQL catalog, your cloud compute | No | | Dune | Yours, written in SQL | Fully, it is your query | SQL, API, enterprise datashare | Enterprise by sales | | DefiLlama | Documented exclusions, open adapters | Yes, open source per metric | Website, repositories | Free | The third column is the one that decides whether a number can be defended. Two of these six let you see the rule, and one of those two is the rule you wrote. **What to note:** cite the platform and the methodology date together, because at least one platform has changed its filter mid-year. --- ## The Provenance Problem Independent agreement between sources is weaker evidence than it looks, because several of these sources are not independent. Messari's own documentation states that it sources stablecoin data from Token Terminal, so a figure confirmed in both is one figure seen twice. Visa Onchain Analytics is built on Allium, so the same applies to any cross-check between them. Documentation drift makes this harder to audit. Visa's September changelog describes a labelled address set of roughly 600 million while its methodology page still cites over 3 million, and a reader comparing a January citation to an October one is comparing two different filters under one name. **What to note:** when two sources agree, check whether one of them buys its data from the other before treating that as confirmation. --- ## How to Choose ### 1\. Decide whether you are citing or deciding A blog post needs a defensible public source, and a product decision needs the underlying rows. Those are different purchases. ### 2\. Require the exclusion rules, not the word adjusted Ask which categories are removed and what share of volume that represents. A platform describing its filter as a simple heuristic has not answered. ### 3\. Get a second estimate from a different filter Artemis against Visa is the useful pairing precisely because they disagree. Two sources sharing one pipeline is not a second estimate. ### 4\. Match delivery to where you work Snowflake-only, SQL catalogs billing your own cloud compute, and warehouse datashares all assume infrastructure you may not have. Confirm this before pricing. ### 5\. Fix your metric vocabulary first Transfer volume, payment volume, adjusted volume and settlement volume are four things, and our list of [**stablecoin metrics**](https://stablecoininsider.org/defi-metrics-for-stablecoins-in-2026/) is a useful starting vocabulary even though individual figures there should be checked against their original sources. **What to note:** write the definition into your own reporting template, so a platform change does not silently change your trend line. --- ## How This List Was Built Inclusion required three things, so that the comparison means something. - Published documentation of what the platform measures, not just a dashboard - Stablecoin-specific coverage available to a business today - Enough published detail to state what the platform does not disclose Several platforms serving this category are not here. Messari appears in the analysis rather than the list because its own documentation states that its stablecoin data comes from Token Terminal, and others were excluded because the measurement basis is not publicly documented. Operators who believe they meet the three criteria above are welcome to send documentation for consideration in the next update. **What to note:** last reviewed against documentation in October 2026, and at least one platform revised its methodology during 2026. --- ## Risks and Limitations - Adjusted and raw volume differ by roughly a factor of five, so the two are not interchangeable in any sentence. - Visa describes its exclusion rules as a heuristic without specifying them, and revised them during 2026. - Visa's methodology page and its changelog state different labelled address counts. - Messari's stablecoin data comes from Token Terminal, so the two are not independent sources. - Token Terminal sums holders across deployments, so one address on two chains counts twice. - Allium's accuracy claim measures indexing fidelity against node data, not the correctness of its adjustments. - Allium's own report names imperfect wallet labelling as a risk in its own figures. --- ## Conclusion The best stablecoin data platform is the one whose filter you can explain to whoever challenges your number. Everything else is a question of delivery and budget. Allium is the enterprise substrate and the one to understand if you cite anyone else's research. Visa Onchain Analytics is the free public reference, Artemis is the second estimate worth having because it disagrees, Token Terminal is the strictest on definitions, Dune hands you the filter, and DefiLlama is the only fully inspectable option. Two habits matter more than the choice. Cite the methodology date alongside the platform, and check whether your second source buys its data from your first. ***Read Next:*** - [**Allium Stablecoins Report 2026**](https://stablecoininsider.org/allium-stablecoins-report-2026/) - [**USDT Is Bigger and Moves Less**](https://stablecoininsider.org/usdt-is-2-5x-bigger-than-usdc-and-moves-3x-less/) - [**DeFi Metrics for Stablecoins**](https://stablecoininsider.org/defi-metrics-for-stablecoins-in-2026/) --- ## FAQs: ### 1\. What is adjusted stablecoin volume? A total that removes transfers judged not to be real economic activity, such as bot arbitrage, market-maker rebalancing, bridging and internal protocol mechanics. On Visa's dashboard the adjusted figure was 817.5 billion dollars against 3.9 trillion unadjusted, removing roughly 79 percent. ### 2\. Why do platforms report different stablecoin volumes? Because each one labels addresses and excludes categories differently, and labelling is a judgement rather than a measurement. Artemis produces a materially higher estimate than Visa on the same chains, and neither figure is wrong so much as differently defined. ### 3\. Which platform should I cite in published research? Visa Onchain Analytics is free, public and widely recognised, which makes it the easiest to cite, and DefiLlama is the most auditable because its adapters are open source. Name the platform and the date in either case, since methodologies change. ### 4\. Can I check a number myself? Yes, with two of these. Dune lets you write the query and read other people's, and DefiLlama publishes an open-source adapter per metric, while the adjusted figures from Allium and Visa are described rather than reproducible. ### 5\. Are these platforms independent of each other? Not entirely, and this matters when cross-checking. Visa Onchain Analytics is built on Allium data, and Messari states that its stablecoin data comes from Token Terminal, so agreement between those pairs is not independent confirmation. --- ***Disclaimer:*** This content is provided for informational and educational purposes only and does not constitute financial, investment, legal, or tax advice; no material herein should be interpreted as a recommendation, endorsement, or solicitation, and readers should conduct their own independent research or consult a qualified professional. Coverage, methodology descriptions, delivery options, certifications and figures are drawn from each platform's own documentation or publications at the time of writing, are not independently verified or reproduced here, and change frequently, including during 2026 in at least one case. Volume, supply and user figures quoted anywhere in this article depend on filtering choices made by the platform that produced them; confirm current methodology and figures directly with each platform before relying on them for research, reporting or commercial decisions.