Previously, on Jepsen, we reviewed Elasticsearch’s progress in addressing data-loss bugs during network partitions. Today, we’ll see Aerospike, an “ACID database”, react violently to a basic partition.
Aerospike is a high-performance, distributed, schema-less, KV store, often deployed in caching, analytics, or ad tech environments. Its five-dimensional data model is similar to Bigtable or Cassandra: namespaces (databases) contain sets (tables) of records, where keys identify records. Each record is a map of bin names to values. Aerospike has put a good deal of work into performance across good-size (~100TB) datasets, and is repositioning itself as a general purpose datastore competitive with, say, MongoDB.
Data is sharded and balanced between servers using a Paxos-based membership algorithm. Stored procedures are available in Lua and allow for MapReduce-style parallel queries. There’s a lot to like here. However, Aerospike makes a dangerous assumption for a distributed datastore: it assumes the network is reliable. In this post, we’ll explore what happens in Aerospike 3.5.4 when the network is not reliable.