Benchmarking BDB, CDB and Tokyo Cabinet on large datasets
dmo.ca/ blog/ Benchmarking BDB, CDB and Tokyo Cabinet on large datasets At my job we have need of a high-performance hash lookup database in our antispam product. It's used to store Bayes tokens for quick lookups on individual scanning systems, and is read-only in the fast path (mail scanning) with updates taking place in another process. For the last few years, we've been using a plain old Berkel
Performance data for LevelDB, Berkley DB and BangDB for Random Operations - High Scalability -
This is a guest post by Sachin Sinha, Founder of Iqlect and developer of BangDB. The goal for the paper is to provide the performances data for following embedded databases under various scenarios for random operations such as write and read. The data is presented in graphical manner to make the data self explanatory to some extent. LevelDB:LevelDB is a fast key-value storage library written at Go
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