Hi, Sorry, I am new to this mailinglist and not sure this question fits, but have I question how to optimize my queries I am experimenting with monetdb for image retrieval, having an image database of 300000 image. At the moment, I am using the Locality Sensitive Hashing method and because I understood from the monetdb documenation that monetdb supports indexing/hash tables, which makes the implementation quiet easy in monetdb. I have for each image 30 buckets with 24 bit strings (int) (should be indexed, assume automatically done by monetdb) I have for each image a feature vector of 1000 real values. I have for each image a unique id together with some info like file name. At the moment, my table is as follows image_id, filename, bucket_1, bucket_2, bucket_3 ... bucket_30, feature_value_1, feature_value_2, ..., feature_value_1000 For Locality Sensitive Hashing, I am performing the following sql query: select * from table where bucket_1 = bitstring or bucket_2 = bitstring or bucket_3 = bitstring or ... bucket_30 = bitstring (limit 1000) These bitstrings are quiet unique, giving me around the 500 images from the entire database. I would also like to obtain the feature vector (so all feature values). At the moment, query and data retrieval times depends but often take around 0.5-1 minute, what are ways to improve this. Does using 2 tables help or storing the feature vector in one column? Ideas are welcome. I am using the MAPI client to retrieve the data. Happy to provide more information if necessary Cheers, Bas Boom University of Edinburgh part of Fish4Knowledge consortium -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.