To achieve high availability in the face of network partitions, many distributed databases adopt eventual consistency, allow temporary conflicts due to concurrent writes, and use some form of per-key logical clock to detect and resolve such conflicts. Furthermore, nodes synchronize periodically to ensure replica convergence in a process called anti-entropy, normally using Merkle Trees. We present the design of DottedDB, a Dynamo-like key-value store, which uses a novel node-wide logical clock framework, overcoming three fundamental limitations of the state of the art: (1) minimize the metadata per key necessary to track causality, avoiding its growth even in the face of node churn; (2) correctly and durably delete keys, with no need for tombstones; (3) offer a lightweight anti-entropy mechanism to converge replicated data, avoiding the need for Merkle Trees. We evaluate DottedDB against MerkleDB, an otherwise identical database, but using per-key logical clocks and Merkle Trees for anti-entropy, to precisely measure the impact of the novel approach. Results show that: causality metadata per object always converges rapidly to only one id-counter pair; distributed deletes are correctly achieved without global coordination and with constant metadata; divergent nodes are synchronized faster, with less memory-footprint and with less communication overhead than using Merkle Trees.

Version vectors (VV) are used pervasively to track dependencies between replica versions in multi-version distributed storage systems. In these systems, VV tend to have a dual functionality: identify a version and encode causal dependencies. In this paper, we show that by maintaining the identifier of the version separate from the causal past, it is possible to verify causality in constant time (instead of O(n) for VV) and to precisely track causality with information with size bounded by the degree of replication, and not by the number of concurrent writers.

Version vectors and their variants play a central role in update tracking in optimistic distributed systems. Existing mechanisms for a variable number of participants use a mapping from identities to integers, and rely on some form of global configuration or distributed naming protocol to assign unique identifiers to each participant. These approaches are incompatible with replica creation under arbitrary partitions, a typical mode of operation in mobile or poorly connected environments. We present an update tracking mechanism that overcomes this limitation; it departs from the traditional mapping and avoids the use of integer counters, while providing all the functionality of version vectors in what concerns version tracking.