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Tech Talk: SevenLabs - Carbon Data Pipeline

By breakpoint-25

Published on 2025-12-12

SevenLabs announces Carbon V1, a Rust framework for building Solana indexers with 5x performance improvements and a modular pipeline approach

The notes below are AI generated and may not be 100% accurate. Watch the video to be sure!

Building indexers on Solana just got significantly easier. SevenLabs' Carbon framework is approaching its V1 release with a remarkable 5x performance boost for historical backfills, promising to transform how developers process and index blockchain data.

Summary

Carbon is a Rust framework designed to simplify the complex task of building Solana indexers. Born from SevenLabs' experience as a development shop on Solana over two years, the team noticed a frustrating pattern: developers were constantly rewriting the same code for data sourcing, decoding, and processing. Carbon aims to solve this by providing a single, modular pipeline where components can be plugged in and configured without starting from scratch.

The framework follows a builder pattern that makes composing data pipelines intuitive. Developers can select their data source (whether historical or real-time), attach decoders that work directly with program IDLs, and add processors for storage or workflow triggers. The entire pipeline can then be executed end-to-end with minimal boilerplate code.

What makes Carbon particularly powerful is its ecosystem integration. The framework supports multiple data sources including GRPC for real-time data and various solutions for historical data. It works with both Anchor and Kinobi IDLs, automatically generating decoder implementations through its CLI tool. This means developers can go from having raw blockchain data to fully decoded, typed updates with minimal manual work.

The upcoming V1 release represents a significant milestone for the project. Beyond the performance improvements, it introduces a stable API, reworked metrics with Prometheus support, and comprehensive documentation. The team is also planning future additions including Clickhouse and Kafka processors, optimized decoders for important programs like SPL-token, and version decoding support.

Key Points:

The Problem Carbon Solves

Solana development shops have long faced a repetitive challenge: every new project requiring blockchain data needed custom code for three distinct tasks—sourcing data (both historical and real-time), decoding it from program IDLs, and processing it for storage or other workflows. This meant teams were essentially rebuilding the same infrastructure repeatedly.

SevenLabs, having operated as a Solana dev shop for approximately two years, observed this pattern across multiple projects and teams in the ecosystem. Rather than continue this inefficient approach, they created Carbon as a unifying framework that handles these common tasks through a modular, pluggable architecture. The framework abstracts away the complexity of data ingestion and decoding, letting developers focus on their specific processing logic.

Modular Pipeline Architecture

Carbon's architecture is built around three core components that can be mixed and matched. Data sources form the input layer, supporting everything from local data dumps to GRPC streams and historical data providers. The framework maintains and publishes traits for various data sources as the ecosystem evolves, including integrations with free historical transaction streaming and vendor solutions like Helius's new RPC endpoints.

The decoding layer transforms raw blockchain data into meaningful, typed structures. This is where Carbon's CLI shines—it can generate complete decoder implementations from any Anchor or Kinobi IDL. Developers simply run the CLI against their program's IDL and receive a crate with all necessary decoding logic. The processing layer then receives these decoded updates, giving developers full access to transaction metadata alongside their program-specific data types.

Performance and V1 Release

The V1 release marks a turning point for Carbon with a stable API across all core crates and proper semantic versioning. Most notably, the update delivers more than 5x performance improvement for raw pipeline operations. This is particularly impactful for historical backfilling scenarios, where developers can now process around 100,000 transactions through their pipeline with decoding and indexing at significantly higher speeds.

The metrics system has also been reworked for better performance. Carbon already supported fully extensible metrics through Prometheus and logging, but the V1 update makes this faster and more efficient. Combined with the upcoming documentation site featuring guides, examples, and best practices, V1 establishes the foundation for Carbon's future development.

CLI and Code Generation

Carbon's command-line interface is central to the developer experience. The scaffold command can generate complete project structures for those just getting started. More importantly, the CLI handles IDL-based code generation, creating decoder implementations that developers can import directly into their pipelines.

A particularly useful feature is the Postgres integration available through a feature flag in generated crates. When enabled, developers get access to pre-built Postgres processors for accounts and instructions. Combined with auto-generated database migrations, this means a complete indexing solution for a Solana program can be set up in just a few lines of code—simply configure a GRPC connection and let the pipeline run.

Future Roadmap

Beyond V1, SevenLabs has ambitious plans for Carbon's evolution. New processors for Clickhouse and Kafka will be generated through CLI commands, always gated behind feature flags to keep the core framework lean. Speed-optimized decoders are planned for critical programs, particularly those in the Solana Program Library like SPL-token.

Version decoding is another planned feature that will allow different decoding logic based on IDL versions and slot ranges—essential for programs that have undergone upgrades. Perhaps most significantly, the team plans to build language-agnostic GRPC streams, opening Carbon's capabilities to teams working in languages other than Rust.

Facts + Figures

  • Carbon has surpassed 500 stars on GitHub, reflecting growing community adoption
  • V1 delivers more than 5x performance improvement for raw pipeline operations
  • Historical backfills can now process approximately 100,000 transactions through the pipeline
  • SevenLabs has been operating as a Solana dev shop for approximately two years
  • Carbon development began about a year ago after recognizing repeated code patterns
  • The framework supports both Anchor and Kinobi IDL formats
  • Multiple data sources are supported including GRPC for real-time and various providers for historical data
  • Helius's "get transactions for address" RPC endpoint is integrated as a data source
  • V1 introduces proper semantic versioning for the first time
  • Prometheus support is included for extensible metrics collection
  • A documentation site with guides, examples, and best practices is coming with V1
  • Future processors planned include Clickhouse and Kafka integrations
  • SPL programs will receive speed-optimized decoder implementations

Top quotes

  • "About a year ago, we realized that a lot of teams were basically just rewriting the same pieces of code."
  • "The goal was to have a single pipeline that is modular and that you can just plug things into."
  • "You'll be able, basically, in a few lines of code index all of your accounts and instructions inside Postgres."
  • "We've had a performance update with more than 5x in row pipeline, which is huge for historical backfilling."
  • "You can have between around 100K that flows through your pipeline and that you then just decode and index."
  • "This V1 will be the foundation for everything that comes next."
  • "Now is a great time if you want to raise issues, or if you have any PR that you want to open."

Questions Answered

What is Carbon and who is it designed for?

Carbon is a Rust framework created by SevenLabs for building Solana indexers. It's designed for developers who need to source, decode, and process blockchain data from Solana programs. Whether you're building analytics dashboards, triggering automated workflows based on on-chain events, or maintaining historical records of program activity, Carbon provides the infrastructure to accomplish these tasks without writing boilerplate code from scratch. The framework is particularly valuable for teams building on Solana who want to focus on their specific application logic rather than rebuilding common data pipeline components.

How does Carbon's modular architecture work?

Carbon uses a builder pattern to compose data pipelines from three main components: data sources, decoders, and processors. You start by selecting your data source—this could be GRPC for real-time data, historical data providers, or even local data dumps. Next, you attach decoders that transform raw blockchain data into typed structures using your program's IDL. Finally, you add processors that determine what happens with the decoded data, whether that's storing it in a database, logging it, or triggering other workflows. Each component is pluggable, meaning you can swap implementations without affecting other parts of your pipeline.

What data sources does Carbon support?

Carbon supports a wide range of data sources that cover both real-time and historical needs. For real-time data, GRPC streams are the primary method. For historical data, the framework has integrated with community solutions that allow free streaming of historical transactions at high speeds. On the vendor side, Carbon supports Helius's "get transactions for address" RPC endpoint. The framework is designed to be extensible, with SevenLabs maintaining and publishing traits for new data sources as the ecosystem evolves. You can also implement custom data source traits if you have specific requirements or a local data dump you need to process.

How do I decode data from my Solana program using Carbon?

Carbon's CLI tool handles decoder generation automatically from your program's IDL. The CLI supports both Anchor and Kinobi IDL formats and generates complete decoder implementations as a separate crate. Once generated, you simply import this crate and add it as an instruction or account pipe in your pipeline. The decoders give you access to fully typed, decoded updates along with all relevant transaction metadata. This eliminates the tedious work of manually deserializing blockchain data and ensures type safety throughout your application.

What's new in Carbon V1?

Version 1 brings several major improvements to Carbon. The most impactful is a 5x performance improvement for raw pipeline operations, which dramatically speeds up historical backfilling. The release also introduces a stable API across all core crates with proper semantic versioning, meaning developers can rely on consistent interfaces going forward. The metrics system has been reworked for better performance while maintaining full Prometheus compatibility. A comprehensive documentation site with guides, examples, and best practices will accompany the release. This version establishes the foundation for future features including Clickhouse and Kafka processors, optimized decoders for SPL programs, and version decoding support.

Can I store indexed data in Postgres without writing custom code?

Yes, Carbon makes Postgres storage remarkably straightforward. When you generate a decoder using the CLI, the resulting crate includes a Postgres feature that you can enable. This gives you access to pre-built account and instruction processors designed for Postgres storage. The generated crate also includes database migrations to create your tables. In practice, this means you can set up a complete indexing solution in just a few lines of code—specify your data source (like a GRPC connection), add your generated decoder, enable the Postgres processor, run migrations, and your pipeline is ready to index all account and instruction updates directly into your database.

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