Cryptocurrency analytics platforms provide deep insights into blockchains, protocols, and projects beyond just token and NFT prices. However, there are significant differences between various platforms and tools.

There are always trade-offs in terms of coverage and accessibility, functionality and flexibility, pricing, and unique features. To help analysts choose the platform that best fits their needs, we compared the top three cryptocurrency analytics platforms:

• Dune Analytics
• Footprint Analytics
• Flipside

When selecting the most suitable tool, analysts can consider the following 11 core aspects:

1. Coverage
2. Balancing Flexibility and Usability
3. Latency
4. Performance
5. Pricing
6. Visualization
7. Data Model
8. NFT Data
9. Tech Stack
10. Off-chain Data Integration
11. API/SDK

We will explore how Dune Analytics, Footprint Analytics, and Flipside perform in these areas and highlight their respective advantages.

Background

Several comprehensive comparison articles on analytics tools have been published before. However, in this article, we will focus exclusively on tools specifically designed for blockchain analytics.

Additionally, instead of discussing each platform individually, we will address each category of evaluation one by one. If you or your team are looking for a solution to a specific problem—such as finding the most cost-effective tool or the platform with the most extensive NFT analytics, you can skip directly to the relevant section.

Coverage

Coverage refers to the number of blockchains or networks and tool indexes, such as Ethereum, Solana, or Boba Network. However, coverage also includes depth, meaning how far back the tool indexes transactions on a given blockchain.

Data engineer and blockchain analyst Primo Data has created one of the best and most up-to-date visualization charts comparing network coverage across different analytics platforms.

Among the top three cryptocurrency analytics platforms, Footprint Analytics has the widest coverage, supporting 20 out of 43 tracked networks. Flipside follows closely with 15 networks, while Dune Analytics lags behind with only 8.

If you only need to analyze major tokens or blockchains such as Bitcoin, Solana, or Ethereum, coverage may not be a critical factor, as all three platforms provide analytics for these mainstream assets.

However, in niche areas such as GameFi, coverage becomes crucial. Many blockchain-based games operate on small, specialized, and sometimes temporary chains, such as DFK Chain, Ronin, and Wax. Footprint Analytics’ extensive coverage makes it the top choice for GameFi analytics, as it is the only platform among the three that provides data on all three of these chains.

Balancing Flexibility and Usability

Due to the open-source nature of Web3 code, setting up a blockchain ETL (Extract, Transform, Load) warehouse and making it available for users to explore independently is relatively easy. The challenging part lies in the interpretation layer—how a platform categorizes all raw data into meaningful classifications while filtering out irrelevant or junk information.

Raw data itself is highly flexible, allowing anyone to define, categorize, and interpret it as they see fit. However, for the vast majority of analysts, this raw data is not readily usable. On the other hand, excessive data simplification limits the ability of teams with advanced needs to create customized, specialized analytics.

Ultimately, all platforms are built on relational databases, meaning SQL serves as the primary tool. To use platforms like Flipside and Dune, users typically require SQL knowledge. Footprint, however, has introduced an additional abstraction layer on top of SQL—essentially an SQL query generator—that provides a drag-and-drop analytics interface. While this interface allows users to construct only simple SQL queries (without stacked queries, correlated subqueries, or window functions), it significantly lowers the barrier to entry. As a result, it serves as an important addition to the overall ecosystem.

Latency

Latency refers to the time required to update data.

In a @carsonbrown67/the-race-for-data-domination-an-evaluation-of-the-todays-top-crypto-analytics-platforms-3cdf83d512fe">deep-dive comparison article published by analyst Carson Brown in October, he compared the latency of several major analytics platforms and found that Dune had the shortest latency among the three platforms, while Footprint Analytics ranked second with slightly longer delays.

Latency is clearly a significant issue, and our engineering team has been actively working to address it. On November 7, Footprint announced several major upgrades. After these upgrades, a new round of queries was conducted on each platform to retrieve the latest Ethereum block, yielding the following results:

Performance

Performance refers to the speed at which users can query data. This is particularly crucial for professional analysts or those who need to process numbers efficiently.

The results show that Flipside was the fastest, Footprint Analytics came second, and Dune ranked third with a response time of 17 seconds.

Pricing

Both Dune and Footprint offer free versions designed for beginners, along with paid plans for advanced users. Footprint’s free version also supports data APIs.

Flipside does not charge any fees. It acts as an intermediary between projects (such as Uniswap and SushiSwap), offering analysis rewards while providing the necessary infrastructure for conducting analytics.

For more details on how rewards are distributed, check this Discord explanation. Each reward is split 50/50 between the platform and the analyst.

Visualization

All platforms provide basic charting functionalities. However, if users want to view data from different perspectives in both dynamic and static forms, Footprint offers these additional options. The table below compares the visualization capabilities of the three platforms:

Data Model

A well-structured data model for blockchain analytics should meet the following criteria:

• Minimize table joins – Users should be able to quickly locate the entities they need to join.
• Reduce comprehension costs – This is a broad requirement. For example, it may include eliminating the need to search for smart contract addresses separately or aggregating raw transactions.
• Optimize indexing – Ensuring tables can be queried quickly is essential.
• Avoid data redundancy – Storing the same information across multiple tables can lead to inconsistencies and errors.
• Ensure data integrity – This can be achieved by using foreign keys and other database tools to prevent anomalies.
• Keep the data model as simple as possible – This is crucial for scalability and maintainability.

All platforms support raw transaction data and allow for comprehensive analysis. Additionally, all platformsprovide tables that store decoded data. However, if users need pre-aggregated statistical tables for quick insights into business metrics, only Footprint offers such tables.

NFT Data

If you are interested in NFT analytics, it is essential to evaluate the coverage of each platform across different networks and marketplaces before making a choice. The following queries return the respective data values.

From the results, Flipside supports the most marketplaces. Footprint provides additional business metrics, such as wash trading detection (Twitter reference), which, like other metrics, can be queried via API.

Tech Stack

Fundamentally, all platforms are built on relational databases. When handling billions or even trillions of rows of data, it is crucial to implement a scalable infrastructure.

All three platforms use SQL as their primary query language, allowing for easy migration of queries with minimal modifications. However, Footprint has introduced an additional abstraction layer on top of SQL, enabling drag-and-drop queries. Moreover, the Jupyter Notebook has recently been adopted as an interface option.

Off-Chain Data Integration

When analyzing on-chain data, the ability to compare it with off-chain data using statistical tools (such as correlation analysis) is crucial. Dune and Footprint both allow users to upload their own tables for real-time analysis within their respective platforms.

Additionally, Footprint provides reference lookup tables (e.g., token_info, protocol_info), enabling users to quickly find tokens by name. Footprint’s extensive coverage of NFT token metadata also makes NFT attribute analysis possible.

API/SDK

For research teams and analysts who do not have strict execution time requirements for one-time data retrieval and only need to embed charts into reports, query execution speed may not be a major concern. However, teams planning software integration require fast query execution (e.g., for transaction history retrieval in popular wallet applications) and an interface to interact with the database.

Dune (Query Engine V2), Flipside, and Footprint all provide an official SQL API, allowing users to migrate any website query to the API. However, this integration method is not the simplest, as it requires pre-constructed SQL queries. To simplify this, Footprint is developing a REST API, allowing users to fetch data with just a button click.

Regarding automated data loading, only Footprint offers an official software infrastructure, enabling users to build fully automated data pipelines.

Among these platforms, only Flipside provides an official SDK, supporting Python and R.