Jepsen: MongoDB 3.6.4
In February 2017, we discussed data loss and fixes in MongoDB 3.4.0-rc3’s v0 and v1 replication protocols. In this Jepsen report, we will verify that MongoDB 3.6.4’s sharded clusters offer comparable safety to non-sharded deployments. We’ll also discuss MongoDB’s new support for causal consistency (CC) in version 3.6.4 and 4.0.0-rc1, and show that sessions prevent anomalies so long as user stick t
Jepsen: Dgraph 1.0.2
Dgraph is a distributed graph database which uses Raft for per-shard replication and a custom transactional protocol, based on Omid, Reloaded, for snapshot-isolated cross-shard transactions. Dgraph claimed to offer snapshot isolation, per-client monotonicity, and linearizability. However, in Dgraph 1.0.2 through 1.0.6, we found multiple deadlocks & crashes in the cluster join and node recovery pro
Consistency Models
This clickable map (adapted from Bailis, Davidson, Fekete et al and Viotti & Vukolic) shows the relationships between common consistency models for concurrent systems. Arrows show the relationship between consistency models. For instance, strict serializable implies both serializability and linearizability, linearizability implies sequential consistency, and so on. Colors show how available each m
Jepsen: Aerospike 3.99.0.3
Aerospike is a high-performance distributed document store. Following up on our 2015 analysis, we explored Aerospike’s new strong-consistency mode, which offers linearizable operations on single records. We confirmed two documented flaws in Aerospike’s homegrown replication algorithm. First, it can lose updates when more than k nodes crash (either concurrently or in sequence). Second, when either
Jepsen: Hazelcast 3.8.3
Hazelcast is a distributed in-memory data grid, providing shared data structures for distributed systems. We show that many of Hazelcast’s distributed data structures are unsafe in the presence of network partitions: updates to maps can be lost, unique IDs may not be unique, atomic objects are not atomic, locks aren’t exclusive, and queues can forget about enqueued elements. Stale and dirty reads
Research Ethics
People rely on Jepsen to help them test their own systems, to make decisions about algorithms, to compare different databases against one another, and to suggest how to work with a particular system’s constraints. To put this work in context, I’d like to talk about Jepsen’s limitations and biases–technical, social, and fiscal. Technical Limitations Jepsen analyses generally consist of running oper
Jepsen: MongoDB 3.4.0-rc3
In April 2015, we discussed stale and dirty reads in MongoDB 2.6.7. However, writes appeared to be safe; update-only workloads with majority write concern were linearizable. This conclusion was not entirely correct. In this Jepsen analysis, we develop new tests which show the MongoDB v0 replication protocol is intrinsically unsafe, allowing the loss of majority-committed documents. In addition, we
Jepsen: CockroachDB beta-20160829
CockroachDB is a distributed, scale-out SQL database which relies on hybrid logical clocks to provide serializability, given semi-synchronized node clocks. In this Jepsen analysis, we’ll discuss multiple serializability violations in CockroachDB beta-20160829 through beta-20160908. As a result of our collaboration, fixes for these issues are included in beta-20160915 and beta-20161013. This work w
Analyses
Get Tested You can hire Jepsen to analyze a database, queue, or other kind of system. Jepsen also offers training and consulting to help you build and extend your own tests. Techniques Jepsen occupies a particular niche of the correctness testing landscape. We emphasize: Opaque-box systems testing: we evaluate real binaries running on real clusters. This allows us to test systems without access to
Distributed Systems Safety Research
About Jepsen Jepsen is an effort to improve the safety of distributed databases, queues, consensus systems, etc. We maintain an open source software library for systems testing, as well as blog posts and conference talks exploring particular systems’ failure modes. In each analysis we explore whether the system lives up to its documentation’s claims, file new bugs, and suggest recommendations for
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Jepsen: Tendermint 0.10.2