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Open-Source Databases · blockchain-etl

ethereum-etl

Ethereum ETL is a Python-based tool that extracts blockchain data from Ethereum (blocks, transactions, tokens, contracts) and converts it into standard formats like CSV and relational databases. It integrates with cloud platforms like Google BigQuery and AWS for large-scale data analysis.

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Source: GitHub — github.com/blockchain-etl/ethereum-etl

3.1k

GitHub stars

904

Forks

Python

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	blockchain-etl/ethereum-etl
Owner	blockchain-etl
Primary language	Python
License	MIT — OSI-approved
Stars	3.1k
Forks	904
Open issues	153
Latest release	v2.4.2 (2024-04-11)
Last updated	2026-01-25
Source	https://github.com/blockchain-etl/ethereum-etl

What ethereum-etl is

Written in Python, Ethereum ETL connects to Ethereum nodes via RPC providers (Infura, Geth, Parity IPC) to extract and transform blockchain state into structured datasets. It supports batch export of blocks/transactions, ERC20/ERC721 transfers, traces, and streaming consumption via Pub/Sub or Kafka.

Quickstart

Get the ethereum-etl source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/blockchain-etl/ethereum-etl.git2cd ethereum-etl3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Ethereum Data Analytics & Business Intelligence

Organizations needing to analyze Ethereum transaction patterns, token flows, and smart contract activity can export structured data directly to BigQuery or data warehouses for dashboards, reporting, and ML pipelines.

Blockchain Compliance & Audit

Compliance teams can extract and archive transaction history, wallet activity, and token transfers in queryable formats to support regulatory reporting, fraud detection, and transaction tracing.

Data Scientists & Research

Academic researchers and data scientists can efficiently download historical Ethereum data in bulk CSV or database format for analysis, model training, and on-chain behavior studies without managing full nodes.

Implementation considerations

Requires active Ethereum node access (Infura, Alchemy, local node) via RPC endpoint; network provider reliability directly impacts export speed.
Large block ranges (e.g., genesis to present) require significant compute time and storage; plan batch sizes and infrastructure (GCP/AWS) accordingly.
Dependency on external RPC providers introduces rate-limiting and availability risk; consider provider redundancy and backup endpoints.
Python environment setup, package dependencies (web3.py, pandas), and cloud SDK credentials must be configured before first use.
Data schema changes on Ethereum (new opcodes, EIP changes) may require tool updates; monitor releases and test upgrades before production deployment.

When to avoid it — and what to weigh

Real-Time Trading or High-Frequency Operations — ETL exports are batch-oriented; latency and throughput may not suit trading algorithms or systems requiring subsecond on-chain data updates. Use direct RPC connections for real-time use cases.
Non-Ethereum Blockchains — Ethereum ETL is blockchain-specific. For multi-chain analysis, alternatives like Nansen or custom tools are required; the project does not natively support Bitcoin, Solana, or other chains.
Minimal DevOps/Infrastructure Expertise — Deployment requires managing Ethereum nodes, cloud credentials, Docker, and provider URIs. Teams without DevOps capability may prefer fully managed analytics platforms like Dune Analytics.
Applications Requiring Real-Time Smart Contract State — ETL focuses on historical transaction data; deriving current contract state requires separate indexing logic. Use The Graph or similar subgraph systems for live smart contract queries.

License & commercial use

Licensed under MIT (Massachusetts Institute of Technology License). MIT is a permissive, OSI-approved open-source license permitting commercial use, modification, and distribution with minimal restrictions.

MIT license permits commercial use, including resale and proprietary derivatives, provided original MIT license and copyright notice are retained. No warranty or support clause in MIT itself; commercial support arrangements are separate business decisions. Internal use, SaaS deployment, and consulting services based on this tool are all commercially viable.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

ETL handles public blockchain data; no confidentiality concerns with data itself. Security considerations include: RPC endpoint authentication (API keys, mTLS) must be protected; cloud credentials (BigQuery, AWS) require proper IAM policies and access controls; exported CSV/database files may be large and need secure storage; dependency vulnerabilities in Python packages (web3.py, pandas) require regular patching. No cryptographic operations are embedded; tool does not manage private keys or sign transactions.

Alternatives to consider

Dune Analytics

Fully managed SaaS platform; no infrastructure required, live dashboards, SQL-friendly abstraction layer. Trade-off: less control, higher cost, vendor lock-in.

The Graph (Subgraphs)

GraphQL-based indexing for smart contracts and real-time state; ideal for live queries and decentralized app backends. Trade-off: requires schema definition, different paradigm than bulk ETL.

ethereum-etl.rs (Rust rewrite)

Same CLI interface, 1.4x faster performance, lower memory footprint. Trade-off: less mature ecosystem, fewer integrations documented.

Software development agency

Build on ethereum-etl with DEV.co software developers

Ethereum ETL simplifies bulk export of Ethereum transaction and token data. Assess your RPC provider strategy, cloud infrastructure, and Python environment readiness, then deploy.

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ethereum-etl FAQ

Do I need to run a full Ethereum node?

No. You can use hosted RPC providers (Infura, Alchemy, QuickNode). A local node is optional for higher throughput or privacy; IPC connections are supported.

How long does it take to export all historical Ethereum data?

Depends on block range, RPC provider rate limits, and hardware. Example: exporting genesis to 500k blocks shown in README. For mainnet (~20M blocks), expect hours to days depending on batch size and parallelization.

Can I use this for non-Ethereum chains?

Not directly. Project is Ethereum-specific. Sister projects exist (ethereum2-etl for Beacon Chain). For other chains, use chain-specific ETL tools or build custom adapters.

Is there a Rust version?

Yes, ethereum-etl.rs is a Rust rewrite maintaining CLI compatibility with ~1.4x speed improvement. Use it for performance-critical batch exports.

Custom software development services

Bringing ethereum-etl into production usually means new services, new interfaces, and new failure modes. DEV.co is a software development agency that builds all three and stays on for the open-source databases maintenance.

Ready to extract blockchain data at scale?

Ethereum ETL simplifies bulk export of Ethereum transaction and token data. Assess your RPC provider strategy, cloud infrastructure, and Python environment readiness, then deploy.

Talk to DEV.co Schedule a Consultation