Scalar DL is a tamper-evident and scalable distributed database. This design document briefly explains the background, design and implementation of Scalar DL.

Background and Objectives

Distributed ledgers or blockchains have been attracting a lot of attention recently, especially in the areas of financial and legal applications. They have gained acceptance due to their tamper-evidence and decentralized control properties. However, the existing platforms do not necessarily handle properties such as finality and scalability well, which are particularly important for mission-critical applications. HyperLedger Fabric [1] applies blockchain to a private network owned by the fixed number of organizations so that ledger states are always finalized unless malicious attacks happen. While Fabric applies interesting endorsement mechanism to avoid non-deterministic execution, its architecture is based on Byzantine-fault tolerant state machine replication (BFT SMR); thus, its performance does not necessarily scale as the number of peers increases. Scalar DL is a practical solution to tackle the challenge in an essentially different approach.

Design Goals

The primary design goals of Scalar DL are to achieve both high tamper-evidence of data and high scalability of performance. We have also taken great care to provide ACID-compliance, exact finality, linearizable consistency, and high availability. The performance of Scalar DL is highly dependent on the underlying database performance, but it can be modified without much effort by replacing the underlying database with one that is suitable for the user’s needs because of its loosely-coupled architecture. Ease of use and simplicity are also part of our main design goals since they are the keys to making Scalar DL scalable.

Fault Model

The assumed fault model behind Scalar DL is byzantine fault [2]. However, with some configurations, it only assumes weak (limited) byzantine fault; that is, the database component assumes byzantine fault but the ledger component assumes only crash fault.

Data Model

Scalar DL abstracts data as a set of assets. An asset can be arbitrary data but is more compatible to being viewed as a historical series of data. For example, assets can range from the tangible (real estate and hardware) to the intangible (contracts and intellectual property).

An asset is composed of one or more asset records where each asset record is identified by an asset ID and an age. An asset record with age M has a cryptographic hash of the previous asset record with age M-1, forming a hash-chain, so that removing or updating an intermediate asset record may be detected by traversing the chain.

There is also a chain structure in between multiple assets. This chain is a relationship constructed by business/application logic. For example in a banking application, payment in between multiple accounts would update the both accounts, which will create such a relationship between assets. In Scalar DL, business logic is digitally signed and tamper evident, and the initial state of an asset is the empty state, which is also regarded as tamper-evident, so that we can deduce the intermediate asset state is also tamper evident as shown below.

Sn = F (Sn-1) 

Si: the state of a set of asset at age i
F: the signed business logic

Thus, assets in Scalar DL can be seen as a DAG of dependencies.

Smart Contract

Scalar DL defines a digitally signed business logic as a Smart Contract, which only a user with access to the signer’s private key can execute. This makes the system easier to detect tampering because the signature can be made only by the owners of private keys.

For more details

A little more details are explained in Scalar DL Technical Overview. Also, please wait for a white paper that we are currently working on for further details.


  • [1] Elli Androulaki, Artem Barger, Vita Bortnikov, Christian Cachin, Konstantinos Christidis, Angelo De Caro, David Enyeart, Christopher Ferris, Gennady Laventman, Yacov Manevich, Srinivasan Muralidharan, Chet Murthy, Binh Nguyen, Manish Sethi, Gari Singh, Keith Smith, Alessandro Sorniotti, Chrysoula Stathakopoulou, Marko Vukolić, Sharon Weed Cocco, Jason Yellick, Hyperledger fabric: a distributed operating system for permissioned blockchains, Proceedings of the Thirteenth EuroSys Conference, April 23-26, 2018, Porto, Portugal.
  • [2] Leslie Lamport, Robert Shostak, Marshall Pease, The Byzantine Generals Problem, ACM Transactions on Programming Languages and Systems (TOPLAS), v.4 n.3, p.382-401, July 1982.