In the last Jepsen post, we found that RethinkDB could lose data when a network partition occurred during cluster reconfiguration. In this analysis, we’ll show that although VoltDB 6.3 claims strict serializability, internal optimizations and bugs lead to stale reads, dirty reads, and even lost updates; fixes are now available in version 6.4. This work was funded by VoltDB, and conducted in accordance with the Jepsen ethics policy.

VoltDB is a distributed SQL database intended for high-throughput transactional workloads on datasets which fit entirely in memory. All data is stored in RAM, but backed by periodic disk snapshots and an on-disk recovery log for crash durability. Data is replicated to at least k+1 nodes to tolerate k failures. Tables may be replicated to every node for fast local reads, or sharded for linear storage scalability.

As an SQL database, VoltDB supports the usual ad-hoc SQL statements, with some caveats (e.g. no auto-increment, no foreign key constraints, etc.) However, its approach to multi-statement transactions is distinct: instead of BEGIN ... COMMIT, VoltDB transactions are expressed as stored procedures, either in SQL or Java. Stored procedures must be deterministic across nodes (a constraint checked by hashing and comparing their resulting SQL statements), which allows VoltDB to pipeline transaction execution given a consensus on transaction order.