Imagine that SKU-22 requires cold storage. Pat notices the database entry showing that we have some SKU-22 in stock and turns the thermostat down to 56F. This turns out to be very unpopular with everybody that works in the building. By the time somebody else checks the database to verify Pat's finding, the data error has been fixed.
This example shows why systems of record should never delete data, even if that data is mistaken. Other parties may have acted on that data, and a key responsibility of data-of-record systems is to provide an audit trail in these situations.
With Datomic, you can make a database query as-of any previous point in time, where time can be specified either as an instant or as a transaction id. If you are following along in code, you probably don't remember the exact instant in time that you made the correction above–and you don't have to. You can query the system for the most recent transactions:
(d/q '[:find (max 3 ?tx) :where [?tx :db/txInstant]] db) => [[[13194139533330 13194139533329 13194139533328]]]
max in find limits the results to the three highest valued (most
recent) transaction ids. Take the smallest of these, and use
to back up past the two "correction" transactions. Now you can see the
data about SKU-22 that justifies Pat's unpopular decision:
;;Your transaction ids may differ (def txid 13194139533328) @(def db-before (d/as-of db txid)) (d/q '[:find ?sku ?count :where [?inv :inv/sku ?sku] [?inv :inv/count ?count]] db-before) => [["SKU-42" 100] ["SKU-42" 1000] ["SKU-21" 7] ["SKU-22" 7]]
In addition to point-in-time auditing, you can also review the entire
history of your data. When you query against a history database
value, the query will return all assertions and retractions,
regardless of when they were in effect. The following query shows the
complete history of
:inv/count data for items by SKU:
(require '[clojure.pprint :as pp]) (def db-hist (d/history db)) (->> (d/q '[:find ?tx ?sku ?val ?op :where [?inv :inv/count ?val ?tx ?op] [?inv :inv/sku ?sku]] db-hist) (sort-by first) (pp/pprint)) => ([13194139534399 "SKU-21" 7 true] [13194139534399 "SKU-42" 100 true] [13194139534399 "SKU-22" 7 true] [13194139534400 "SKU-22" 7 false] [13194139534402 "SKU-42" 1000 true] [13194139534402 "SKU-42" 100 false])
?op is true for assertions, and false for retractions. You can
- Transaction …399 set the count for three SKUs.
- Transaction …400 retracted the count for SKU-22.
- Transaction …402 "changed" the count for SKU-42.
Deleting System (Optional)
You have finished the tutorial. If you are done with your Datomic System, you can follow the instructions for Deleting a System.
In this tutorial you have seen how to assert and retract datoms, create schema, pull hierarchical data, and query with Datalog. You have also seen how the accumulate-only model facilitates as-of and history views of the database.
While this tutorial has introduced several key ideas, it has only scratched the surface of Datomic's capabilities. As you build your database, consult the reference section of docs.datomic.com for more in-depth coverage.