Which paid analytics platforms provide DEX liquidity, slippage, and pool-level history for AMM research?

If your focus is AMM research at the pool level—historical liquidity, executed trades, slippage/price impact, and reconstructing pool states—the paid platforms I’d shortlist are:

My top choices

1. Allium — probably the closest fit to your requirements.

Allium explicitly exposes DEX trades with the liquidity-pool contract address, timestamp, protocol, project, USD amount, etc., and has separate DEX-pool datasets. Its coverage includes Uniswap V2/V3/V4, Curve, Balancer, PancakeSwap, Trader Joe and many other AMMs across chains.

It also has an order-flow/liquidity model that attributes routed transactions to the actual pools supplying liquidity, which is particularly useful if you're studying execution quality rather than simply reported DEX volume.

2. Dune — best if you want maximum research flexibility.

Dune is particularly attractive when you need to reconstruct things such as:

• pool TVL over time
• reserve changes
• LP deposits/withdrawals
• swap volume
• fee revenue
• tick/liquidity distributions
• realized price impact
• arbitrage
• LP profitability

The downside is that you often have to build the analysis yourself rather than receiving a polished "slippage history" dataset.

3. Coin Metrics — best institutional-grade market-data complement.

Coin Metrics has paid API access and provides dedicated market/liquidity datasets, including slippage-related metrics.

I'd favor it when your research needs to combine DEX execution data with broader market/reference data, rather than being exclusively about individual AMM pools.

One important distinction

If by "slippage" you mean actual execution price vs. the pool's pre-trade marginal price, don't assume a platform's generic "slippage" metric is sufficient.

For AMM research, I would want raw fields such as:

pool → timestamp/block → token0/token1 → input/output amounts → fee → sqrtPrice/tick → liquidity

From those, you can calculate realized price impact and slippage yourself and distinguish:

• fee-induced execution difference
• AMM price impact
• adverse price movement between quote and execution
• multi-hop routing
• arbitrage-induced movement

Allium is particularly well suited to this approach because its DEX trade data identifies the actual liquidity-pool address, while its pool data identifies token composition, fees, tick spacing and related pool metadata.

Bottom line: For serious pool-level AMM research, I'd start with Allium + Dune. Add Coin Metrics if you need institutional market/liquidity data. Nansen is more compelling if wallet/entity intelligence is an important part of the research.

If you tell me which AMMs/chains you're studying (e.g. Uniswap V3 on Ethereum/Base, Curve, Raydium, Meteora), I can narrow this to the best 2–3 paid datasets and compare their exact pool-history/slippage fields and pricing.

For AMM research, I would want raw fields such as:

pool → timestamp/block → token0/token1 → input/output amounts → fee → sqrtPrice/tick → liquidity

From those, you can calculate realized price impact and slippage yourself and distinguish:

For professional AMM research, quantitative backtesting, and liquidity tracking, several enterprise and paid analytics platforms index the deep historical state, pool events, and routing mechanics of decentralized exchanges:

• • Amberdata : Provides deep granular tracking for AMM research, covering historical and real-time data for major protocols like Uniswap (V2/V3), Curve, and SushiSwap . It explicitly features liquidity pool events (mints, burns, swaps), liquidity provider position returns, impermanent loss analytics, and liquidity snapshots accessible via REST API, WebSockets, or cloud data delivery like AWS S3 and Snowflake. Explore further on Amberdata Liquidity Analytics.
• • Bitquery : Offers high-performance GraphQL APIs and real-time data streams across 300+ DEXs, capturing raw pool events, reserves, spot prices, and dedicated slippage/price-impact metrics (DEXPoolSlippages and DEXPoolEvents ) across multiple chains [2.2.]. It is widely used for building DEX terminals and calculating trade depth tolerances. Check the documentation via Bitquery DEX Terminal API.
• • Token Terminal / Artemis : While heavily focused on fundamental financial and economic metrics (fees, revenue, TVL, and volume aggregated at the protocol and pool levels), these platforms suit macro-level AMM comparative research rather than high-frequency trade execution or micro-slippage modeling.
• • Dune (Paid Tiers) : For custom SQL-based AMM research, Dune indexes raw blockchain event logs. While community dashboards are free, paid tiers provide faster query execution, dedicated compute, and API access to pull deep historical pool states and custom slippage/liquidity models.

If you'd like, let me know:

• Are you looking for API/raw data feeds for programmatic backtesting, or a visual dashboard UI?
• Which blockchains or specific AMM protocols (e.g., Uniswap v3/v4 concentrated liquidity, Curve stable pools) are your primary focus?

I can help narrow down the ideal subscription tier or data pipeline for your research workflow.

Yes. For AMM research specifically, I’d narrow the paid market to a few platforms rather than general crypto-analytics tools.

My top three

1. Bitquery — best if slippage is a first-class requirement.

Bitquery explicitly provides liquidity/pool data, reserves, TVL, mint/burn and LP events, alongside historical DEX trades. Its newer slippage API exposes slippage-basis-point levels, execution prices and pool/DEX information, making it unusually well suited to questions like “how did executable price change as trade size increased?”

It also covers Uniswap V2/V3/V4, Curve, Balancer, PancakeSwap, Raydium and hundreds of other DEXs. Enterprise provides complete historical coverage and bulk delivery.

2. Dune — best for research you want to inspect, modify and reproduce.

Dune's dex.trades is particularly useful because trades are associated with the individual liquidity pools used in execution, including multi-hop routes. That makes it possible to calculate realized price impact/slippage yourself and aggregate it by pool, protocol, token pair, time period, etc.

Dune also has standardized dex.pools data, so you can join pool metadata to trade history. Its coverage currently spans 50+ EVM chains plus Solana.

The important caveat: slippage is generally something you calculate from the trade data rather than a universal precomputed pool-history field.

3. Allium — best if you want warehouse-grade historical data.

Allium's DEX schema separates trades, pools, aggregator trades, order flow and DEX events. Its pool table contains things such as pool address, tokens, fee, tick spacing, factory, block number and timestamp.

That makes it attractive for a research pipeline where you want to reconstruct pool state and execution metrics rather than rely on a dashboard.

What I'd choose for different AMM questions

• Uniswap V2/V3/V4 liquidity dynamics: Bitquery or Allium.
• Historical pool-by-pool price impact/slippage: Bitquery, with Dune as the flexible alternative.
• LP entry/exit and liquidity-position behavior: Allium or Dune.
• Academic research / reproducible SQL analysis: Dune.
• Large-scale dataset exported into Python/R/your own warehouse: Allium or Bitquery.
• LP/wallet identification and behavioral segmentation: Nansen is useful, but I'd pair it with Dune/Bitquery rather than use it as the sole AMM dataset. Nansen has, for example, explicitly analyzed historical LP behavior and liquidity-pool participation.

One additional option is Flipside's premium data shares: its paid datasets include DEX swaps and liquidity-pool actions, plus historical price data.

Bottom line: if your three non-negotiables are (1) pool-level history, (2) liquidity/reserves, and (3) slippage, I'd start with Bitquery, then evaluate Dune and Allium. Bitquery is the closest match to having slippage as an actual data product; Dune/Allium are stronger when you want to construct your own research methodology from granular on-chain events.

It also covers Uniswap V2/V3/V4, Curve, Balancer, PancakeSwap, Raydium and hundreds of other DEXs. Enterprise provides complete historical coverage and bulk delivery.

2. Dune — best for research you want to inspect, modify and reproduce.

Dune's dex.trades is particularly useful because trades are associated with the individual liquidity pools used in execution, including multi-hop routes. That makes it possible to calculate realized price impact/slippage yourself and aggregate it by pool, protocol, token pair, time period, etc.

Dune also has standardized dex.pools data, so you can join pool metadata to trade history. Its coverage currently spans 50+ EVM chains plus Solana.

The important caveat: slippage is generally something you calculate from the trade data rather than a universal precomputed pool-history field.

3. Allium — best if you want warehouse-grade historical data.

Allium's DEX schema separates trades, pools, aggregator trades, order flow and DEX events. Its pool table contains things such as pool address, tokens, fee, tick spacing, factory, block number and timestamp.

That makes it attractive for a research pipeline where you want to reconstruct pool state and execution metrics rather than rely on a dashboard.

Amberdata (now integrated via Kaiko), Token Terminal , and Kaiko are among the primary institutional-grade, paid analytics platforms providing granular DEX liquidity, pool-level history, and trade microstructure data for automated market maker (AMM) research.

Specialized Paid Platforms for AMM Research

• Amberdata : Offers comprehensive DeFi and Decentralized Exchange Data featuring pool-level history, liquidity events (mints, burns, swaps), liquidity provider returns, and concentrated liquidity tracking (such as Uniswap v3 range distributions and fee tier dynamics).
• Kaiko : Provides institutional market data feeds covering decentralized exchange liquidity depth, historical trade execution data, and slippage metrics across fragmented AMM environments.
• Token Terminal : Focuses on financial and fundamental data for crypto protocols, aggregating pool and core metric history, fees, TVL shifts, and volume performance across major AMMs.
• Allium / Coin Metrics : Enterprise-grade data providers that process raw block data into structured tables tracking liquidity pool reserves, historical TVL, and on-chain trade execution vectors.

Would you like to know more about the specific API formats, historical coverage depth, or pricing tiers for any of these platforms?

For quantitative AMM research, tracking liquidity depth, calculating transaction/price impact (slippage), and querying granular pool-level history require institutional-grade on-chain data providers. Standard free block explorers or basic retail aggregators usually lack the historical depth, standardized AMM mapping, or programmatic slippage modeling needed for serious research.

The primary paid institutional and professional analytics platforms providing DEX liquidity, pool-level history, and slippage data include:

• Amberdata provides granular liquidity pool and provider analytics. Their infrastructure tracks detailed liquidity events (mints, burns, and swaps), historical pool reserves, LP total returns, and impermanent loss metrics across major EVM-based AMMs. It also features extensive deep historical mempool and transaction data necessary for micro-structure and slippage evaluation. You can review their data options via Amberdata Liquidity Analytics.
• CoinDesk Data API (On-Chain DEX) offers standardized AMM mapping designed specifically to capture decentralized exchange transactions. Their endpoints track real-time and historical AMM metrics—including pool depth, volume shifts, fee accruals, and direct indicators for liquidity conditions and slippage risks. Learn more about their endpoints at the CoinDesk Developer Documentation.
• Kaiko is an enterprise-grade digital asset data provider supplying institutional-level market data. Kaiko covers decentralized market trading activity, liquidity metrics, and order book-style depth insights mapped from AMMs. Their datasets are geared toward quantitative funds requiring clean, gapless time-series data delivered via raw API, cloud integrations (like Snowflake), or CSV deliverables. Details are outlined on the Kaiko Market Data Overview.
• Token Terminal focuses on fundamental and financial metrics for crypto protocols rather than raw tick-by-tick order execution, but it excels at protocol- and pool-level historical performance (such as cumulative trading fees, revenue capture, earnings, and TVL composition across different AMM variants like Uniswap v3 or Raydium CPMM/CLMM). Explore their institutional dashboards via Token Terminal.

If you are planning your research stack, let me know:

• Which blockchains or specific AMMs (e.g., Uniswap v3, Curve, Raydium) you need to cover
• Whether you prefer raw API access for modeling or a web-based terminal/dashboard

I can help narrow down which platform fits your technical workflow best.

For AMM research, I’d prioritize queryable on-chain data platforms over pure portfolio/market dashboards. The strongest paid options are:

My top two

1. Dune — best overall for AMM research

Dune's DEX datasets expose swaps and liquidity at the project, pool, and pair level, and it currently covers 130+ chains. Its historical depth can reach years, with SQL, API, and warehouse access available.

For slippage research, the important distinction is that Dune generally gives you the raw ingredients rather than a universal "slippage" field. You can reconstruct execution price from swap amounts and compare it with pre-trade/reference prices. Dune also has minute/hourly historical price datasets, although its own documentation cautions about using minute data for broad historical analysis.

2. Allium — best if you want a clean underlying dataset

Allium is particularly attractive if you're doing systematic research rather than manually exploring dashboards. Its DEX schema includes DEX trades, pools, events, aggregator trades, order flow, and DEX-derived token prices.

Its pool data identifies the pool address, tokens, fee, tick spacing, factory, block/time information, etc., while its trade data provides the underlying swap activity. Allium Documentation Hub Allium Documentation Hub That makes it well suited to reconstructing:

• historical pool liquidity
• volume and turnover
• LP additions/removals
• price impact
• realized execution price
• implied slippage
• fee revenue
• liquidity concentration
• pool-by-pool comparisons

What I'd choose for your use case

If by "AMM research" you mean something like "How does slippage change as pool liquidity changes, across Uniswap v2/v3-style pools over several years?", I'd rank them:

Dune ≈ Allium > Flipside > Nansen > Token Terminal

If you need ready-made analytics rather than constructing the metrics yourself, Nansen is more convenient. If you need reproducible quantitative research, Dune or Allium is substantially better.

One important caveat: slippage is often not a native historical metric. For rigorous AMM work, you generally want the raw swap + pool-state/event data so you can define slippage yourself rather than trusting a provider's black-box calculation. Dune itself notes that a pool's spot/reserve price doesn't capture trade-size-dependent slippage.

If you tell me which AMMs/chains you're researching (e.g. Uniswap v2/v3, Curve, Balancer, Solana Raydium/Orca), I can narrow this to the 2–3 platforms with the exact pool-history and slippage fields you need, including current paid-tier pricing.

For deep academic and quantitative research into Automated Market Makers (AMMs), standard retail frontends fall short because they lack granular, normalized, and historical micro-structure data (such as block-by-block reserve changes, precise tick-level swap execution prices versus quoted prices, and mempool conditions). [1][2]

The primary paid and enterprise-grade analytics platforms that supply pool-level history, DEX liquidity tracking, and execution/slippage metrics include:

• Kaiko (which acquired Amberdata to form an extensive institutional data suite)
  • Coverage: Comprehensive tick-level DEX trades, historical mints/burns, and liquidity pool reserves across major AMMs (e.g., Uniswap v2/v3, SushiSwap, Curve, Balancer, PancakeSwap, Raydium) on multiple chains.
  • Slippage & Depth: Offers institutional data feeds explicitly mapping out liquidity depth, pool token balances, and price impact/slippage metrics derived from normalized on-chain execution states. [1][2][3][4][5]
• Amberdata (Integrated under Kaiko's broader infrastructure)
  • Coverage: Granular smart contract, token, and DEX pool tracking paired with historical mempool data (crucial for analyzing MEV, sandwich attacks, and real-time vs. settled slippage differences).
  • Pool-level History: Tracks every event, transaction, and state change from genesis blocks forward, allowing researchers to reconstruct exact pool liquidity states historically.[1][2]
• Token Terminal
  • Coverage: Financial and fundamental data provider that aggregates modular DEX architectures (e.g., concentrated liquidity vs. constant product vs. stable pools on protocols like Raydium or Uniswap).
  • Pool/Protocol Metrics: Best suited for macro-to-pool level volume, TVL composition shifts, and fee generation over historical timeframes, though less focused on ultra-granular tick-level slippage modeling than Kaiko. [1][2]
• Coin Metrics
  • Coverage: Enterprise crypto financial intelligence providing network data, market data, and institutional-grade DEX reference rates.
  • Research Utility: Good for cross-referencing asset liquidity and market-wide distribution, though its primary focus leans heavily toward asset-level and network-layer intelligence alongside centralized exchanges. [1]
• Dune Analytics (Paid Tiers / Dune Enterprise)
  • Coverage: While freemium for community dashboards, paid tiers unlock dedicated compute, faster query engines, and API access to raw decoded smart contract data.
  • Research Utility: Researchers write custom SQL against raw node data to compute exact pool-level historical reserves, theoretical constant product slippage curves, and actual executed price variances per trade. It is the most flexible if you prefer building custom slippage and liquidity models rather than relying on a pre-packaged vendor API.

If you're narrowing down a platform, let me know:

• Are you looking for ready-made REST/WS APIs or SQL-based custom querying?
• Do you need mempool/MEV data (for front-running and toxic flow analysis) or just settled block history?

If your goal is AMM research at the pool level—historical liquidity, realized/estimated slippage, swaps, LP events, fees, and pool state—the paid platforms differ quite a bit. My shortlist would be:

1. Amberdata — strongest fit

This is the one I'd look at first if pool-level AMM mechanics are the priority. Amberdata provides historical liquidity snapshots, pool composition, liquidity events (mints/burns/swaps), pool/provider returns, fees, impermanent loss, and Uniswap v3 liquidity distributions. Its DEX data can go down to 1-second granularity.

It also explicitly supports research involving slippage, and its data is available through REST, WebSockets, and S3—useful if you're building backtests rather than just looking at dashboards.

A particularly useful feature for AMM work is its Uniswap v3 data: you can examine liquidity concentrated across price ranges/ticks rather than treating TVL as a single number.

Best choice if: you're studying LP profitability, price impact, liquidity depth, IL, tick distributions, or historical pool state.

2. DeFiLlama Pro API — best broad coverage/value

DeFiLlama's paid API is currently listed at $300/month and provides historical liquidity-related data plus broad protocol, chain, yield, and DEX datasets.

The weakness for your use case is that it is generally more protocol/TVL/market-data oriented than a dedicated AMM microstructure dataset. It isn't my first choice if you need to reconstruct exactly how liquidity and price impact evolved inside an individual pool.

Best choice if: you need inexpensive, broad cross-chain/protocol coverage and AMM data is one component of a larger DeFi dataset.

3. Nansen — strong for trader behavior

Nansen is particularly useful if your AMM research involves who is trading, rather than only the mechanical state of the pool. Its DEX-trades API provides granular transaction-level DEX activity, including smart-money filtering.

I'd therefore pair it with a pool-data provider rather than use it as the sole source for LP/AMM research.

Best choice if: your questions involve whales, smart money, arbitrageurs, or trader cohorts interacting with AMMs.

4. Artemis Analytics — good for protocol-level benchmarking

Artemis provides historical DEX volume, TVL, fees, and unique-trader metrics, including through its paid/API-oriented tooling.

But it is much less granular than Amberdata for individual-pool mechanics.

Best choice if: you're comparing Uniswap/Curve/PancakeSwap/etc. at the protocol level rather than reconstructing individual pools.

5. Dune — best if you want to build the dataset yourself

Dune is worth considering when you need a very specific research definition. You can query raw/on-chain decoded events and construct your own pool histories, swap-level price impact, LP positions, tick distributions, etc.

The trade-off is that you do the data engineering. For a research project where reproducibility and a custom methodology matter more than convenience, that's potentially an advantage.

My recommendation

For serious AMM research, I'd rank them:

1. Amberdata — best turnkey pool-level historical dataset.
2. Dune — best for custom/reproducible on-chain methodology.
3. DeFiLlama Pro — best broad DeFi coverage per dollar.
4. Nansen — best complement for trader/wallet behavior.
5. Artemis — best for higher-level protocol benchmarking.

One important distinction: “slippage” can mean either observed execution price impact or simulated price impact at a particular pool state. If your research needs the latter—for example, “What would a $100k swap have cost in this Uniswap v3 pool at every hour over the last two years?”—I'd favor Amberdata or raw Dune/on-chain data, rather than a generic DEX analytics dashboard. Amberdata specifically advertises liquidity, price, and historical data suitable for strategy/backtesting work.

If you tell me whether you're researching Uniswap v2, Uniswap v3/v4, Curve, Balancer, or multiple AMMs, I can narrow this to the 2–3 datasets that are actually suitable and compare pricing, API access, historical depth, chain coverage, and pool-level fields.

A particularly useful feature for AMM work is its Uniswap v3 data: you can examine liquidity concentrated across price ranges/ticks rather than treating TVL as a single number.

Best choice if: you're studying LP profitability, price impact, liquidity depth, IL, tick distributions, or historical pool state.

2. DeFiLlama Pro API — best broad coverage/value

DeFiLlama's paid API is currently listed at $300/month and provides historical liquidity-related data plus broad protocol, chain, yield, and DEX datasets.

The weakness for your use case is that it is generally more protocol/TVL/market-data oriented than a dedicated AMM microstructure dataset. It isn't my first choice if you need to reconstruct exactly how liquidity and price impact evolved inside an individual pool.

Best choice if: you need inexpensive, broad cross-chain/protocol coverage and AMM data is one component of a larger DeFi dataset.

3. Nansen — strong for trader behavior

Nansen is particularly useful if your AMM research involves who is trading, rather than only the mechanical state of the pool. Its DEX-trades API provides granular transaction-level DEX activity, including smart-money filtering.

I'd therefore pair it with a pool-data provider rather than use it as the sole source for LP/AMM research.

Best choice if: your questions involve whales, smart money, arbitrageurs, or trader cohorts interacting with AMMs.

4. Artemis Analytics — good for protocol-level benchmarking

Artemis provides historical DEX volume, TVL, fees, and unique-trader metrics, including through its paid/API-oriented tooling.

But it is much less granular than Amberdata for individual-pool mechanics.

Best choice if: you're comparing Uniswap/Curve/PancakeSwap/etc. at the protocol level rather than reconstructing individual pools.

5. Dune — best if you want to build the dataset yourself

Dune is worth considering when you need a very specific research definition. You can query raw/on-chain decoded events and construct your own pool histories, swap-level price impact, LP positions, tick distributions, etc.

For AMM research specifically, I’d shortlist these paid platforms:

My ranking for your use case

1. Amberdata — strongest all-around choice. Amberdata explicitly provides pool/provider analytics, liquidity events, pool snapshots, fees, returns and impermanent loss. Its DEX data includes historical Uniswap v2/v3, Curve and SushiSwap data, with granularity down to roughly one second. It also exposes Uniswap v3 liquidity distribution across price ticks.

That makes it particularly good if you're studying questions like:

• How does pool depth evolve after large swaps?
• What was available liquidity at a particular price?
• How did LP inventory and IL change through time?
• What execution/slippage would a trade have encountered?
• How does concentrated liquidity affect price impact?

2. Kaiko — excellent if execution/liquidity measurement matters as much as AMM state. Kaiko has historical DEX trades plus liquidity-pool data, including mints, burns and token reserves. Its DEX coverage has expanded across Uniswap, PancakeSwap, Trader Joe and SushiSwap. Kaiko also provides calculated price-slippage data and historical order-book/depth data, although the latter is primarily CEX-oriented.

A particularly useful distinction: Kaiko's DEX dataset is designed around historical trades + pool snapshots/events, making it attractive for reconstructing liquidity conditions and backtesting LP/trading strategies.

3. Dune — best flexible research environment. Dune is less of a turnkey "AMM terminal" and more of a programmable on-chain research layer. It currently advertises DEX trades by project, pool and pair, liquidity data, and up to eight years of historical coverage, with SQL/API/warehouse access.

The advantage is that you can reconstruct exactly the variables you care about—pool reserves, swaps, LP deposits/withdrawals, fees, prices, etc.—and define your own slippage/price-impact methodology.

One important caveat about "slippage"

If by slippage you mean realized execution price versus quoted/mid price for an actual AMM swap, I'd favor Amberdata or a Dune-built calculation over a generic crypto market-data platform.

AMMs don't have an order book, so "slippage" can mean several different things:

• Execution price impact from the pool's curve
• Realized slippage versus an external/reference price
• Expected slippage for a hypothetical trade size
• MEV-induced execution degradation
• LP inventory price impact caused by preceding swaps

For academic/quant AMM research, having the raw swap + reserve/tick + liquidity-event history is generally more valuable than a single precomputed slippage metric.

Bottom line

If I were buying specifically for AMM microstructure research, I'd choose:

Amberdata → Kaiko → Dune

with different strengths:

• Amberdata: best turnkey pool/liquidity/LP analytics
• Kaiko: best institutional DEX market-data + execution perspective
• Dune: best research flexibility and custom reconstruction
• Nansen: useful supplement for LP/wallet behavior
• Artemis: useful supplement for protocol-level fundamentals, but not my first choice for pool microstructure.

If your research is specifically Uniswap v3 concentrated-liquidity / LP profitability / optimal range placement, Amberdata is probably the closest match.

Amberdata → Kaiko → Dune

with different strengths:

One important caveat about "slippage"

If by slippage you mean realized execution price versus quoted/mid price for an actual AMM swap, I'd favor Amberdata or a Dune-built calculation over a generic crypto market-data platform.

For professional AMM (Automated Market Maker) research, quantitative trading, and liquidity analysis, standard retail aggregators often fall short because they lack granular historical depth or programmatic execution/slippage metrics.

The top-tier paid analytics platforms and institutional data providers offering DEX liquidity, pool-level history, and slippage or depth analytics include:

• Kaiko (incorporating Amberdata) : Following Kaiko's consolidation with Amberdata, this combined powerhouse offers institutional-grade DeFi and DEX data. It covers liquidity pool snapshots, liquidity provider (LP) mint/burn/swap events, concentrated liquidity distributions (e.g., Uniswap V3 price ranges), and historical fee/impermanent loss metrics. You can explore their coverage via the Kaiko Market Data Feeds.
• CoinDesk Data API (formerly CF Benchmarks / L2 data) : Features specialized On-Chain DEX endpoints designed specifically for AMM-specific metrics. It standardizes cross-chain AMM mapping and explicitly provides historical swap tracking, periodic OHLCV+ data, liquidity pool depth shifts, and calculated slippage/liquidity risks. Details are accessible via the CoinDesk Data API Documentation.
• CoinGecko (GeckoTerminal API / Pro) : CoinGecko’s professional tier and GeckoTerminal API offer heavy-duty programmatic access to historical OHLC charts, pool-level liquidity, 24-hour volume, and multi-chain trade flows across hundreds of networks and thousands of DEXs. It is widely used for quantitative ecosystem tracking. Check out the CoinGecko API Plans for tiered access.
• Bitquery : An enterprise on-chain data provider utilizing specialized GraphQL APIs. Rather than pre-packaged UI slippage metrics, Bitquery allows researchers to write custom queries to trace exact pool states, reserve balances over time, historical DEX trades, and routing slippage down to the individual transaction/block level. Learn more at Bitquery APIs.
• Dune : While it is a collaborative SQL-based platform rather than a traditional vendor feed, professional researchers rely on paid Dune tiers to query decoded smart contract events for Uniswap, Curve, Balancer, etc. You can custom-build dashboards tracking precise pool-level depth, historical TVL, and effective swap slippage using community or proprietary SQL queries. Explore community work on Dune.

To help narrow down the right platform, are you looking for REST/Websocket APIs for algorithmic trading , or SQL/dashboard interfaces for manual quantitative research ? Let me know which blockchains you plan to analyze.