There are many astronomical databases available for downloading astronomical data.
Most follow the International Virtual Observatory Alliance (IVOA, https://ivoa.net) standards (and in particular the Table Access Protocol, or TAP138).
With TAP, it is possible to submit your queries via a command-line downloader (for example,
curl) to only get specific tables, targets (rows in a table) or measurements (columns in a table): you do not have to download the full table (which can be very large in some cases)!
These customizations are done through the Astronomical Data Query Language (ADQL139).
Therefore, if you are sufficiently familiar with TAP and ADQL, you can easily custom-download any part of an online dataset. However, you also need to keep a record of the URLs of each database and in many cases, the commands will become long and hard/buggy to type on the command-line. On the other hand, most astronomers do not know TAP or ADQL at all, and are forced to go to the database’s web page which is slow (it needs to download so many images, and has too much annoying information), requires manual interaction (further making it slow and buggy), and cannot be automated.
Gnuastro’s Query program is designed to be the middle-man in this process: it provides a simple high-level interface to let you specify your constraints on what you want to download. It then internally constructs the command to download the data based on your inputs and runs it to download your desired data. Query also prints the full command before it executes it (if not called with --quiet). Also, if you ask for a FITS output table, the full command is written into its 0-th extension along with other input parameters to query (all Gnuastro programs generally keep their input configuration parameters as FITS keywords in the zero-th output). You can see it with Gnuastro’s Fits program, like below:
$ astfits query-output.fits -h0
With the full command used to download the dataset, you only need a minimal knowledge of ADQL to do lower-level customizations on your downloaded dataset. You can simply copy that command and change the parts of the query string you want: ADQL is very powerful! For example, you can ask the server to do mathematical operations on the columns and apply selections after those operations, or combine/match multiple datasets. We will try to add high-level interfaces for such capabilities, but generally, do not limit yourself to the high-level operations (that cannot cover everything!).