Performance: look in list or sql query

I developed a software with PyQt and sqlite to manage scientific articles. Each article is stored in the sqlite database, and comes from a particular journal.

Sometimes, I need to perform some verifications on the articles of a journal. So I build two lists, one containing the DOI of the articles (a DOI is just a unique id for an article), and one containing booleans, True if the articles are ok, False if the articles are not:

def listDoi(self, journal_abb):

    """Function to get the doi from the database.
    Also returns a list of booleans to check if the data are complete"""

    list_doi = []
    list_ok = []

    query = QtSql.QSqlQuery(self.bdd)
    query.prepare("SELECT * FROM papers WHERE journal=?")
    query.addBindValue(journal_abb)
    query.exec_()

    while query.next():
        record = query.record()
        list_doi.append(record.value('doi'))

        if record.value('graphical_abstract') != "Empty":
            list_ok.append(True)
        else:
            list_ok.append(False)

    return list_doi, list_ok

This function returns the two lists. The lists can contain ~2000 items each. After that, to check if an article is ok, I just check if it is in the two lists.

So I wonder, because performance matters here: what is faster/better/more economic:

• build the two lists, and check if the article is present in the two lists
• write the function in another way: checkArticle(doi_article), and the function would perform a SQL query for each article

What about the speed and the space in RAM ?