Question: I am trying to create a key/value database with 300,000,000 key/value pairs of 8 bytes each (both for the key and the value). The requirement is to have a very fast key/value mechanism which can query about 500,000 entries per second.

I tried BDB, Tokyo DB, Kyoto DB, and levelDB and they all perform very bad when it comes to databases at that size. (Their performance is not even close to their benchmarked rate at 1,000,000 entries).

I cannot store my database in memory because of hardware limitations (32 bit software), so memcached is out of the question.

I cannot use external server software as well (only a database module), and there is no need for multi-user support at all. Of course server software cannot hold 500,000 queries per second from a single endpoint anyways, so that leaves out Redis, Tokyo tyrant, etc.

Answer: 
David Segleau, here. Product Manager for Berkeley DB. 

The most common problem with BDB performance is that people don't configure the cache size, leaving it at the default, which is pretty small. The second most common problem is that people write application behavior emulators that do random look-ups (even though their application is not really completely random) which forces them to read data out of cache. The random I/O then takes them down a path of conclusions about performance that are not based on the simulated application rather than the actual application behavior. 

From your description, I'm not sure if your running into these common problems or maybe into something else entirely. In any case, our experience is that Berkeley DB tends to perform and scale very well. We'd be happy to help you identify any bottlenecks and improve your BDB application throughput. The best place to get help in this regard would be on the BDB forums at: <http://forums.oracle.com/forums/forum.jspa?forumID=271>. When you post to the forum it would be useful to show the critical query segments of your application code and the db\_stat output showing the performance of the database environment. 

It's likely that you will want to use BDB HA/Replication in order to load balance the queries across multiple servers. 500K queries/second is probably going to require a larger multi-core server or a series of smaller replicated servers. We've frequently seen BDB applications with 100-200K queries/second on commodity hardware, but 500K queries per second on 300M records in a 32-bit application is likely going to require some careful tuning. I'd suggest focusing on optimizing the performance of a the queries on the BDB application running on a single node, and then use HA to distribute that load across multiple systems in order to scale your query/second throughput. 

I hope that helps. 

Good luck with your application. 

Regards,

Dave
We use [Redis](http://redis.io/). Written in C, its only slightly more complicated than memcached by design. Never tried to use that many rows but for us latency is very important and it handles those latencies well and lets us store the data in the disk

Here is a [bench mark blog entry](http://antirez.com/post/redis-memcached-benchmark.html), comparing redis and memcached.