This covers read-write performance for the insert benchmark. Other issues are open for load performance (SERVER-32707) and full scan performance (SERVER-32711).

I will start with results from inMemory-16 (database in memory, 16 clients, 16 collections) and the test where each writer is limited to 100 inserts/second, there are 16 collections, 16 query clients and 16 writer clients with a query/writer pair per collection.

The first table has throughput and HW efficiency metrics:

• ips.av - average insert rate, the target is 1600 given the rate limits, but because of artifacts in my Python code the max is ~1584.
• qps.av - the average query rate
• wkb/i - KB written to storage per insert
• Mcpu/q - CPU overhead per query, alas this includes CPU used for queries and inserts
• size - database size in GB at test end
• rss - mysqld/mongod process size at test end in GB
• wmb/s - storage write MB/s
• cpu - average CPU utilization from vmstat us and sy columns

From these results:

• both engines sustain the target write rate
• InnoDB gets ~2.2X more QPS
• WiredTiger uses ~2.3X more CPU per query

ips.av  qps.av  wkb/i   Mcpu/q  size    rss     wmb/s   cpu     engine
1584    31386   36.09   1184    116     103.5   57.2    37.2    WiredTiger-3.6.0
1584    67772   42.50    518    113     121.9   67.3    35.1    InnoDB-5.7.17

The worst case response times are:

• WiredTiger : ~0.5 seconds for insert, ~0.38 seconds for query
• InnoDB: ~0.01 seconds for insert, ~0.009 seconds for query