You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: README.md
+20-19Lines changed: 20 additions & 19 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -55,14 +55,19 @@ more declarative and composable than SQL, e.g. the automatic implicit joins seem
55
55
to be its killer feature. In addition, the recursive rules feature of Datalog
56
56
makes it suitable for graph processing and deductive reasoning.
57
57
58
-
The feature set of Datomic® may not be a good fit for some use cases. One thing that may [confuse some users](https://vvvvalvalval.github.io/posts/2017-07-08-Datomic-this-is-not-the-history-youre-looking-for.html) is its [temporal features](https://docs.datomic.com/cloud/whatis/data-model.html#time-model). To keep things simple and familiar, Datalevin behaves the same way as most other databases: when data are deleted, they are gone. Datalevin also follows the widely accepted principles of ACID, instead of introducing [unusual semantics](https://jepsen.io/analyses/datomic-pro-1.0.7075).
59
-
60
-
Datalevin started out as a port of
61
-
[Datascript](https://github.com/tonsky/datascript) in-memory Datalog database to
62
-
[LMDB](https://en.wikipedia.org/wiki/Lightning_Memory-Mapped_Database) for
63
-
persistence. We then added a [cost-based query optimizer](doc/query.md),
64
-
resulting in query performance [competitive](benchmarks/JOB-bench) against SQL
65
-
RDBMS such as PostgreSQL.
58
+
The feature set of Datomic® may not be a good fit for some use cases. One thing
0 commit comments