0.18.0

• Fixed DB and Datom pprinting (#287)
• Fixed cases when upsert resolves to tempid (#285)
• Throw on tempid in :db.fn/cas (#264)
• distinct aggregate returns set not a vector (thx @jdf-id-au)
• Ability to run tests with Kaocha
• [ BREAKING ] Some internals of datascript.arrays, datascript.btset and datascript.Datom type has changed

Performance optimizations for JVM version:

• Reimplemented btset in Java with transients and better performance
• Extracted btset to [persistent-sorted-set "0.1.0"]
• Used raw ints in Datom intead of wrapped Integers, added stored in tx sign

Numbers I get on my 3.2 GHz i7-8700B (median time per test, ms):

version	add-1	add-5	add-all	init	retract-5	q1	q2	q3	q4	qpred1	qpred2
0.17.1-jvm	795.8	670.7	651.8	79.4	617.5	2.3	5.4	8.2	13.1	7.1	27.3
0.18.0-jvm	625.2	450.9	401.8	21.8	389.5	1.9	5.4	8.2	13.3	7.3	28.9
0.9.5703-datomic	1693.9	737.9	528.5	---	1420.9	2.8	5.2	7.3	9.3	12.8	15.5
0.18.0-v8	1231.6	963.1	930.3	76.5	809.1	6.4	15.2	23.8	33.6	24.2	24.5

Tests are as follows:

Test	Description
add-1	Add 100k datoms to an empty DB, one datom per transaction
add-5	Add 20k entities to an empty DB, 5 datoms per transaction, 100k datoms total
add-all	Add 20k entities to an empty DB in a single transaction, 100k datoms total
init	“Fast” datascript DB creation from an already sorted array of datoms (used in DB deserialization), 100k datoms
retract-5	Retract 20k entities from a DB with 100k datoms. Each entity removes 5 datoms. 1 entity per tx.
q1	Query with 1 clause over a DB with 100k datoms, ~12k tuples in resultset [:find ?e :where [?e :name "Ivan"]]
q2	Query with 2 clauses, 1 join, ~12k tuples [:find ?e ?a :where [?e :name "Ivan"] [?e :age ?a]]
q3	Query with 3 clauses, 2 joins, ~6k tuples [:find ?e ?a :where [?e :name "Ivan"] [?e :age ?a] [?e :sex :male]]
q4	Query with 4 clauses, 3 joins, ~6k tuples [:find ?e ?l ?a :where [?e :name "Ivan"] [?e :last-name ?l] [?e :age ?a] [?e :sex :male]]
qpred1	Query with a predicate, ~50k tuples [:find ?e ?s :where [?e :salary ?s] [(> ?s 50000)]]
qpred2	Query with a predicate and dynamic input, ~50k tuples [:find ?e ?s :in $ ?min_s :where [?e :salary ?s] [(> ?s ?min_s)]]

For Datomic an datomic:mem:// database was used.

What we see:

• 20..40% faster transactions,
• 75% faster deserialization (db-init),
• No significant change on queries,
• JVM transactions are more than twice as fast as V8,
• JVM queries are 3-4 times as fast as V8,
• DataScript transactions are 25..70% faster that Datomic in-memory. Query times vary.