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ADR-065: Store V2


  • Feb 14, 2023: Initial Draft (@alexanderbez)
  • Dec 21, 2023: Updates after implementation (@alexanderbez)




The storage and state primitives that Cosmos SDK based applications have used have by and large not changed since the launch of the inaugural Cosmos Hub. The demands and needs of Cosmos SDK based applications, from both developer and client UX perspectives, have evolved and outgrown the ecosystem since these primitives were first introduced.

Over time as these applications have gained significant adoption, many critical shortcomings and flaws have been exposed in the state and storage primitives of the Cosmos SDK.

In order to keep up with the evolving demands and needs of both clients and developers, a major overhaul to these primitives are necessary.


The Cosmos SDK provides application developers with various storage primitives for dealing with application state. Specifically, each module contains its own merkle commitment data structure -- an IAVL tree. In this data structure, a module can store and retrieve key-value pairs along with Merkle commitments, i.e. proofs, to those key-value pairs indicating that they do or do not exist in the global application state. This data structure is the base layer KVStore.

In addition, the SDK provides abstractions on top of this Merkle data structure. Namely, a root multi-store (RMS) is a collection of each module's KVStore. Through the RMS, the application can serve queries and provide proofs to clients in addition to provide a module access to its own unique KVStore though the use of StoreKey, which is an OCAP primitive.

There are further layers of abstraction that sit between the RMS and the underlying IAVL KVStore. A GasKVStore is responsible for tracking gas IO consumption for state machine reads and writes. A CacheKVStore is responsible for providing a way to cache reads and buffer writes to make state transitions atomic, e.g. transaction execution or governance proposal execution.

There are a few critical drawbacks to these layers of abstraction and the overall design of storage in the Cosmos SDK:

  • Since each module has its own IAVL KVStore, commitments are not atomic
    • Note, we can still allow modules to have their own IAVL KVStore, but the IAVL library will need to support the ability to pass a DB instance as an argument to various IAVL APIs.
  • Since IAVL is responsible for both state storage and commitment, running an archive node becomes increasingly expensive as disk space grows exponentially.
  • As the size of a network increases, various performance bottlenecks start to emerge in many areas such as query performance, network upgrades, state migrations, and general application performance.
  • Developer UX is poor as it does not allow application developers to experiment with different types of approaches to storage and commitments, along with the complications of many layers of abstractions referenced above.

See the Storage Discussion for more information.


There was a previous attempt to refactor the storage layer described in ADR-040. However, this approach mainly stems on the short comings of IAVL and various performance issues around it. While there was a (partial) implementation of ADR-040, it was never adopted for a variety of reasons, such as the reliance on using an SMT, which was more in a research phase, and some design choices that couldn't be fully agreed upon, such as the snap-shotting mechanism that would result in massive state bloat.


We propose to build upon some of the great ideas introduced in ADR-040, while being a bit more flexible with the underlying implementations and overall less intrusive. Specifically, we propose to:

  • Separate the concerns of state commitment (SC), needed for consensus, and state storage (SS), needed for state machine and clients.
  • Reduce layers of abstractions necessary between the RMS and underlying stores.
  • Remove unnecessary store types and implementations such as CacheKVStore.
  • Simplify the branching logic.
  • Ensure the RootStore interface remains as lightweight as possible.
  • Allow application developers to easily swap out SS and SC backends.

Furthermore, we will keep IAVL as the default SC backend for the time being. While we might not fully settle on the use of IAVL in the long term, we do not have strong empirical evidence to suggest a better alternative. Given that the SDK provides interfaces for stores, it should be sufficient to change the backing commitment store in the future should evidence arise to warrant a better alternative. However there is promising work being done to IAVL that should result in significant performance improvement [1,2].

Note, we will provide applications with the ability to use IAVL v1 and IAVL v2 as either SC backend, with the latter showing extremely promising performance improvements over IAVL v0 and v1, at the cost of a state migration.

Separating SS and SC

By separating SS and SC, it will allow for us to optimize against primary use cases and access patterns to state. Specifically, The SS layer will be responsible for direct access to data in the form of (key, value) pairs, whereas the SC layer (e.g. IAVL) will be responsible for committing to data and providing Merkle proofs.

State Commitment (SC)

A foremost design goal is that SC backends should be easily swappable, i.e. not necessarily IAVL. To this end, the scope of SC has been reduced, it must only:

  • Provide a stateful root app hash for height h resulting from applying a batch of key-value set/deletes to height h-1.
  • Fulfill (though not necessarily provide) historical proofs for all heights < h.
  • Provide an API for snapshot create/restore to fulfill state sync requests.

An SC implementation may choose not to provide historical proofs past height h - n (n can be 0) due to the time and space constraints, but since store v2 defines an API for historical proofs there should be at least one configuration of a given SC backend which supports this.

State Storage (SS)

The goal of SS is to provide a modular storage backend, i.e. multiple implementations, to facilitate storing versioned raw key/value pairs in a fast embedded database. The responsibility and functions of SS include the following:

  • Provided fast and efficient queries for versioned raw key/value pairs
  • Provide versioned CRUD operations
  • Provide versioned batching functionality
  • Provide versioned iteration (forward and reverse) functionality
  • Provide pruning functionality

All of the functionality provided by an SS backend should work under a versioned scheme, i.e. a user should be able to get, store, and iterate over keys for the latest and historical versions efficiently and a store key, which is used for name-spacing purposes.

We propose to have three defaulting SS backends for applications to choose from:

  • RocksDB
    • CGO based
    • Usage of User-Defined Timestamps as a built-in versioning mechanism
  • PebbleDB
    • Native
    • Manual implementation of MVCC keys for versioning
  • SQLite
    • CGO based
    • Single table for all state

Since operators might want pruning strategies to differ in SS compared to SC, e.g. having a very tight pruning strategy in SC while having a looser pruning strategy for SS, we propose to introduce an additional pruning configuration, with parameters that are identical to what exists in the SDK today, and allow operators to control the pruning strategy of the SS layer independently of the SC layer.

Note, the SC pruning strategy must be congruent with the operator's state sync configuration. This is so as to allow state sync snapshots to execute successfully, otherwise, a snapshot could be triggered on a height that is not available in SC.

State Sync

The state sync process should be largely unaffected by the separation of the SC and SS layers. However, if a node syncs via state sync, the SS layer of the node will not have the state synced height available, since the IAVL import process is not setup in way to easily allow direct key/value insertion.

We propose a simple SnapshotManager that consumes and produces snapshots. SC backends will be responsible for providing a snapshot of the state at a given height and both SS and SC consume snapshots to restore state.


We will define a RootStore interface and default implementation that will be the primary interface for the application to interact with. The RootStore will be responsible for housing SS and SC backends. Specifically, a RootStore will provide the following functionality:

  • Manage commitment of state (both SS and SC)
  • Provide modules access to state
  • Query delegation (i.e. get a value for a <key, height> tuple)
  • Providing commitment proofs

Store Keys

Naturally, if a single SC tree is used in all RootStore implementations, then the notion of a store key becomes entirely useless. However, we cannot dictate or predicate how all applications will implement their RooStore (if they choose to).

Since an app can choose to have multiple SC trees, we need to keep the notion of store keys. Unlike store v1, we represent store keys as simple strings as opposed to concrete types to provide OCAP functionality. The store key strings act to solely provide key prefixing/namespacing functionality for modules.


Since the SS layer is naturally a storage layer only, without any commitments to (key, value) pairs, it cannot provide Merkle proofs to clients during queries.

So providing inclusion and exclusion proofs, via a CommitmentOp type, will be the responsibility of the SC backend. Retrieving proofs will be done through the a RootStore, which will internally route the request to the SC backend.


Before ABCI 2.0, specifically before FinalizeBlock was introduced, the flow of state commitment in BaseApp was defined by writes being written to the RootMultiStore and then a single Commit call on the RootMultiStore during the ABCI Commit method.

With the advent of ABCI 2.0, the commitment flow has now changed to WorkingHash being called during FinalizeBlock and then Commit being called on ABCI Commit. Note, WorkingHash does not actually commit state to disk, but rather computes an uncommitted work-in-progress hash, which is returned in FinalizeBlock. Then, during the ABCI Commit phase, the state is finally flushed to disk.

In store v2, we must respect this flow. Thus, a caller is expected to call WorkingHash during FinalizeBlock, which takes the latest changeset in the RootStore, writes that to the SC tree in a single batch and returns a hash. Finally, during the ABCI Commit phase, we call Commit on the RootStore which commits the SC tree and flushes the changeset to the SS backend.


As a result of a new store V2 package, we should expect to see improved performance for queries and transactions due to the separation of concerns. We should also expect to see improved developer UX around experimentation of commitment schemes and storage backends for further performance, in addition to a reduced amount of abstraction around KVStores making operations such as caching and state branching more intuitive.

However, due to the proposed design, there are drawbacks around providing state proofs for historical queries.

Backwards Compatibility

This ADR proposes changes to the storage implementation in the Cosmos SDK through an entirely new package. Interfaces may be borrowed and extended from existing types that exist in store, but no existing implementations or interfaces will be broken or modified.


  • Improved performance of independent SS and SC layers
  • Reduced layers of abstraction making storage primitives easier to understand
  • Atomic commitments for SC
  • Redesign of storage types and interfaces will allow for greater experimentation such as different physical storage backends and different commitment schemes for different application modules


  • Providing proofs for historical state is challenging


  • Removal of OCAP-based store keys in favor of simple strings for state retrieval and name-spacing. We consider this neutral as removal of OCAP functionality can be seen as a negative, however, we're simply moving the OCAP functionality upstream to the KVStore service. The SS and SC layers shouldn't have to concern themselves with OCAP responsibilities.
  • Keeping IAVL as the primary commitment data structure, although drastic performance improvements are being made

Further Discussions

Module Storage Control

Many modules store secondary indexes that are typically solely used to support client queries, but are actually not needed for the state machine's state transitions. What this means is that these indexes technically have no reason to exist in the SC layer at all, as they take up unnecessary space. It is worth exploring what an API would look like to allow modules to indicate what (key, value) pairs they want to be persisted in the SC layer, implicitly indicating the SS layer as well, as opposed to just persisting the (key, value) pair only in the SS layer.

Historical State Proofs

It is not clear what the importance or demand is within the community of providing commitment proofs for historical state. While solutions can be devised such as rebuilding trees on the fly based on state snapshots, it is not clear what the performance implications are for such solutions.