Some folks have asked whether Cassandra or Riak in last-write-wins mode are monotonically consistent, or whether they can guarantee read-your-writes, and so on. This is a fascinating question, and leads to all sorts of interesting properties about clocks and causality.

There are two families of clocks in distributed systems. The first are often termed wall clocks, which correspond roughly to the time obtained by looking at a clock on the wall. Most commonly, a process finds the wall-time clock via gettimeofday(), which is maintained by the operating system using a combination of hardware timers and NTP–a network time synchronization service. On POSIX-compatible systems, this clock returns integers which map to real moments in time via a certain standard, like UTC, POSIX time, or less commonly, TAI or GPS.

Previously in Jepsen, we discussed MongoDB. Today, we’ll see how last-write-wins in Riak can lead to unbounded data loss.

Write contention occurs when two people try to update the same piece of data at the same time.

Major thanks to John Muellerleile (@jrecursive) for his help in crafting this.

Actually, don’t expose pretty much any database directly to untrusted connections. You’re begging for denial-of-service issues; even if the operations are semantically valid, they’re running on a physical substrate with real limits.

As a part of the exciting series of events (long story…) around our riak cluster this week, we switched over to riak-pipe mapreduce. Usually, when a node is down mapreduce times shoot through the roof, which causes slow behavior and even timeouts on the API. Riak-pipe changes that: our API latency for mapreduce-heavy requests like feeds and comments fell from 3-7 seconds to a stable 600ms. Still high, but at least tolerable.

The riak-users list receives regular questions about how to secure a Riak cluster. This is an overview of the security problem, and some general techniques to approach it.

Theory