Storing and searching for data in data stores

A method of storing data in a data store, the data store comprising:

• a first data set;
• and
• a second data set,
• wherein the method comprises:
• storing data in association with a data item in the first and/or second data set;
• applying the second data set as an overlay of the first data set, and
• storing overlay metadata, the overlay metadata being indicative of the second data set being an overlay of the first data set.

A method of searching for machine learning model data in a database, the database comprising:

• live state;
• and
• an overlay state,
• wherein the method comprises:
• searching for a key in the live and/or overlay state, the key being associated with one or more entities in relation to which real-time anomaly detection is being performed;
• and
• in response to said searching finding the key, returning machine learning model data stored in association with the key, the machine learning model data comprising parameter data and/or state data for a machine learning model to be used to perform said real-time anomaly detection,
• wherein, if the key is found in the live state and if the key was updated in the live state after the overlay state became an overlay of the live state, said returning comprises returning first machine learning model data stored in association with the key in the live state,
• wherein, if the key is found in the live and overlay states and if the overlay state became an overlay of the live state after the key was updated in the live state, said returning comprises returning second machine learning model data stored in association with the key in the overlay state, and
• identifying the overlay state based on overlay metadata, the overlay metadata being indicative of the overlay state being an overlay of the live state.