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@avalabsofficial is thrilled to announce the developer preview of Firewood, a multi-year in-house R&D effort to write a state-of-the-art database optimized for storing Merkleized blockchain state from scratch in Rust.
github.com/ava-labs/firewood
Like the #Avalanche HyperSDK, we are opting to develop Firewood in the open before it is complete/production-ready because we know collaboration with the Avalanche Community will supercharge development and lead to a more powerful/capable database.
The developer preview of Firewood being made available today includes much of the core functionality of the database but is not quite ready for Virtual Machine integration (almost there 😉).
You can check out the roadmap for the production launch here: github.com/ava-labs/firewood#roadmap
So...why make a new database (especially from scratch)? 🤔
As many across the space have pointed out, efficient state management is one of the primary bottlenecks to scaling blockchains to reach global scale.
Firewood addresses this bottleneck by reducing the overhead of inserting, modifying, storing, and deleting Merkleized state.
Firewood, unlike many other mechanisms used to manage blockchain state today, is not built on top of a generic key-value store such as LevelDB/RocksDB and manipulates Merkle Trie state directly on-disk.
Firewood uses the trie structure of the data as an index on-disk that never needs to be compacted (similar to a B+ Tree-based database). Firewood also cleans up old state in-place and avoid async pruning/reference counting of unused trie nodes.
Many projects, including #Avalanche, use some form of a trie for storing state because it allows for quick post-execution result comparison (using the root of the trie) and for verifiable data sync between untrusted peers (blobs of data can be quickly verified to be in trie).
This choice, however, is not without tradeoffs. There are theoretical inefficiencies of using Merkle Tries for this task, like the increasingly large number of “inner” trie nodes that must be read from disk and updated per value modification ...
... or the hash-based addressing of nodes that can result in “random” writes/reads all over disk, which puts immense strain on the databases used to persist them (even when performing concurrent, batched modifications every X blocks).
Projects that employ Merkle Tries have relied on existing KV databases, like LevelDB or RocksDB, to efficiently manage this workload even though they are unaware and unoptimized for how the Trie-structured data is written/read during block verification/state sync.
This “misalignment” leads, in practice, to significant overhead of either disk I/O (constant compaction), size (not tracking whether state is still used), and serialization/deserialization of Trie data structures to support high-throughput blockchain workloads.
Firewood, a replacement for the LevelDB/RocksDB + Merkle Trie overlay typically used in blockchain projects, is built from the ground up for efficiently storing and reading Merkleized blockchain state under load.
Efficient, in this context, means [1] only storing the active state on-disk (overwriting state that is no longer used on-the-fly), [2] using the structure of the Merkle Trie to index data on-disk directly instead of a separate LSM Tree (which avoids any compaction) ...
... and [3] location-aware storage of Trie data that is often read at the same time, and [4] fast but still crash-recoverable using a Write-Ahead-Log.
Over the coming months, we will release a series of reproducible benchmarks comparing the performance of Firewood to other blockchain databases, including our own MerkleDB, and provide an example integration into one of the VMs we maintain.
Firewood and MerkleDB will share a common Merkle Trie format that will allow them to be used interchangeably with a re-genesis event. The final goal of all this work is the eventual integration of Firewood into all Virtual Machines (X/P/C/HyperSDK) that Ava Labs maintains.
There is a TON of room to contribute to Firewood, especially if you are familiar with low-level disk access primitives/trie optimizations.
You can view a list of outstanding tasks here if you are intrigued: github.com/ava-labs/firewood#roadmap
Thanks to @Tederminant, @rkuris, @m_s_p_h_x, @_richardpringle, and Dan Sover for their contributions to this project over the past few years.
We'll talk about this project at length at the next Developer Community Call! See you there!