  In-memory key-value stores provide consistent low-latency access to all
objects which is important for interactive large-scale applications like social
media networks or online graph analytics and also opens up new application
areas. But, when storing the data in RAM on thousands of servers one has to
consider server failures. Only a few in-memory key-value stores provide
automatic online recovery of failed servers. The most prominent example of
these systems is RAMCloud. Another system with sophisticated fault-tolerance
mechanisms is DXRAM which is optimized for small data objects. In this report,
we detail the remote replication process which is based on logs, investigate
selection strategies for the reorganization of these logs and evaluate the
reorganization performance for sequential, random, zipf and hot-and-cold
distributions in DXRAM. This is also the first time DXRAM's backup system is
evaluated with high speed I/O devices, specifically with 56 GBit/s InfiniBand
interconnect and PCI-e SSDs. Furthermore, we discuss the copyset replica
distribution to reduce the probability for data loss and the adaptations to the
original approach for DXRAM.
