Modern database systems employ Snapshot Isolation to implement concurrency control and isolationbecause it promises superior query performance compared to lock-based alternatives. Furthermore, Snapshot Isolation never blocks readers, which is an important property for modern information systems, which have mixed workloads of heavy OLAP queries and short update transactions. This paper revisits the problem of implementing Snapshot Isolation in a distributed database system and makes three important contributions. First, a complete definition of Distributed Snapshot Isolation is given, thereby extending existing definitions from the literature. Based on this definition, a set of criteria is proposed to efficiently implement Snapshot Isolation in a distributed system. Second, the design space of alternative methods to implement Distributed Snapshot Isolation is presented based on this set of criteria. Third, a new approach to implement Distributed Snapshot Isolation is devised; we refer to this approach as Incremental. The results of comprehensive performance experiments with the TPC-C benchmark show that the Incremental approach significantly outperforms any other known method from the literature. Furthermore, the Incremental approach requires no a priori knowledge of which nodes of a distributed system are involved in executing a transaction. Also, the Incremental approach can execute transactions that involve data from a single node only with the same efficiency as a centralized database system. This way, the Incremental approach takes advantage of sharding or other ways to improve data locality. The cost for synchronizing transactions in a distributed system is only paid by transactions that actually involve data from several nodes. All these properties make the Incremental approach more practical than related methods proposed in the literature.