sqlhbenchmarks is a sibling benchmarking package for github.com/nofeaturesonlybugs/sqlh. I decided to break the benchmarks out of sqlh because:
- The benchmark code is rather verbose and greatly increases the code base for
sqlh. - Keeping the benchmark code in
sqlhincreases the number of dependencies insqlheven though it's not using them for anything practical.
My primary goals with my benchmark testing were to evaluate:
- Is
sqlhcomparable in performance to currently accepted and widely used packages? - What are the weak areas where I can come back later for optimizations?
- What is the true cost of
reflectwhen pointed at a real database when other factors start to matter (network IO, disk IO at the database server)? - To act as something of a stress test by working with record sets of various sizes.
I'll summarize my results with the following:
- I think
sqlh.Scanneris roughly on par with existing packages and APIs; thus I feel confident using it in my applications anywhere I'd have considered usingsqlxorsqlscan. model.Modelsis probably sufficient for small to medium applications but is lacking in a few benchmarks (not to mention the somewhat limited current feature set). I plan to use it in my small to medium sized applications if that's worth anything to you.- Once you factor in a real database the cost of
reflectstarts to dwindle.
If you have any desire to repeat these benchmarks for your environment or as part of evaluating which SQL package to use in Go:
- Create a
TEST_POSTGRESenvironment variable with a correct DSN forlib/pqto run the Postgres tests. The user in the DSN will need to be able to perform someALTER TABLEstatements; seeschema.gofor the exact statements. - Create a
TEST_SQLITEenvironment variable with a correct DSN for Sqlite. Out of the box this package usesmodernc.org/sqlite; you can make slight alterations tofunctions_sqlite.goto point it atmattninstead.
My model.Models type only supports grammars with a RETURNING clause; therefore to benchmark Sqlite I needed to use version 3.35. Originally I was using the github.com/mattn package (and a specific commit for Sqlite 3.35) but was having trouble when switching back and forth between Windows and Debian for benchmarks. Eventually I substituted github.com/mattn's Sqlite for modernc.org/sqlite. This satisfied my desire of having something other than Postgres to benchmark against however I do not use Sqlite professionally; I don't know if the modernc version of Sqlite is production ready (seems to be experimental). Even though I do not present them here I will say the mattn Sqlite benchmarks were more performant when I did have it working.
Since gorm was relatively easy to point at Postgres I included it in the lib/pq driver benchmarks. I did not feel like struggling to get gorm to behave with modernc Sqlite or sqlmock so it is not present in those benchmarks.
gorm has very good performance when inserting or updating slices of records. Obviously it is using some type of bulk operation internally when asked to work with slices of records. In such benchmarks where I've included gorm it is not really a fair comparison -- the other libraries could probably achieve similar results if written to do so. However this improved performance with gorm "just worked" and required no extra effort on my part. I felt that was noteworthy and included it in such benchmarks even if the comparison is unfair. Kudos to the gorm team in this regard.
squirrel was an interesting experience. I'd had no experience with the package prior to including it in my benchmarks. I do find it to be an improvement in placing query arguments next to where they're used in the query, especially when creating UPDATE statements. I'm not overly fond of the introduction of new types to handle things like prepared statements although I understand the reasoning. squirrel is generally more memory hungry than other packages.
Further - since this is my first time using squirrel - it's possible I may have made mistakes in setting it up for prepared statements in the relevant benchmarks. If anyone happens to check my work and finds errors please let me know and I will update the benchmarks.
goos: windows
goarch: amd64
pkg: github.com/nofeaturesonlybugs/sqlh/benchmarks
cpu: Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz
The following tests:
- Use
sqlmockfor setting up a mock database. - Perform
SELECT * FROM table LIMIT %vwhere the limits are: 5, 50, 100, 500, 1000, & 10000 - And scan into the following struct:
type SaleReport struct {
Id int `json:"id" db:"pk"`
CreatedTime string `json:"created_time" db:"created_tmz"`
ModifiedTime string `json:"modified_time" db:"modified_tmz"`
Price int `json:"price" db:"price"`
Quantity int `json:"quantity" db:"quantity"`
Total int `json:"total" db:"total"`
CustomerId int `json:"customer_id" db:"customer_id"`
CustomerFirst string `json:"customer_first" db:"customer_first"`
CustomerLast string `json:"customer_last" db:"customer_last"`
VendorId int `json:"vendor_id" db:"vendor_id"`
VendorName string `json:"vendor_name" db:"vendor_name"`
VendorDescription string `json:"vendor_description" db:"vendor_description"`
VendorContactId int `json:"vendor_contact_id" db:"vendor_contact_id"`
VendorContactFirst string `json:"vendor_contact_first" db:"vendor_contact_first"`
VendorContactLast string `json:"vendor_contact_last" db:"vendor_contact_last"`
}My interpretation of the results:
- Without a real database the cost of
reflectis more pronounced for small record selections. - Objectively
sqlh.Scanneris the worst performing although not by much. There's three reasons this may be the case:setand thereforesqlhdoes not useFieldByNamemethods inreflectdue to a bug in thereflectpackage.setinstantiates deeply nested structs if they are pointers andnilset's struct traversal when requesting fields by mapped names could be improved; I have some thoughts on how but nothing concrete as of yet.
# records
database/sql_5_rows-8 10000 103287 ns/op 2917 B/op 36 allocs/op
sqlx_5_rows-8 5990 247959 ns/op 3607 B/op 39 allocs/op
scany_5_rows-8 4126 327388 ns/op 3086 B/op 40 allocs/op
sqlh_5_rows-8 3156 403795 ns/op 3832 B/op 43 allocs/op
# 50 records
database/sql_50_rows-8 2790 459121 ns/op 2902 B/op 36 allocs/op
sqlx_50_rows-8 2626 495046 ns/op 3623 B/op 39 allocs/op
scany_50_rows-8 2392 543458 ns/op 3128 B/op 40 allocs/op
sqlh_50_rows-8 2046 604777 ns/op 3864 B/op 43 allocs/op
# 100 records
database/sql_100_rows-8 1966 697026 ns/op 2920 B/op 36 allocs/op
sqlx_100_rows-8 1551 766337 ns/op 3663 B/op 39 allocs/op
scany_100_rows-8 1596 732904 ns/op 3118 B/op 40 allocs/op
sqlh_100_rows-8 1444 761937 ns/op 3911 B/op 43 allocs/op
# 500 records
database/sql_500_rows-8 1528 819504 ns/op 3008 B/op 36 allocs/op
sqlx_500_rows-8 1519 889164 ns/op 3677 B/op 39 allocs/op
scany_500_rows-8 1333 1041175 ns/op 3247 B/op 41 allocs/op
sqlh_500_rows-8 1345 996992 ns/op 4036 B/op 44 allocs/op
# 1,000 records
database/sql_1000_rows-8 1388 944315 ns/op 3037 B/op 36 allocs/op
sqlx_1000_rows-8 1232 966885 ns/op 3795 B/op 40 allocs/op
scany_1000_rows-8 1230 975264 ns/op 3457 B/op 42 allocs/op
sqlh_1000_rows-8 1134 998770 ns/op 4259 B/op 46 allocs/op
# 10,000 records
database/sql_10000_rows-8 1081 1174419 ns/op 4684 B/op 45 allocs/op
sqlx_10000_rows-8 970 1169252 ns/op 6331 B/op 60 allocs/op
scany_10000_rows-8 1065 1131304 ns/op 7770 B/op 68 allocs/op
sqlh_10000_rows-8 1003 1190989 ns/op 8940 B/op 83 allocs/opThe following tests:
- Are pointed at a local network instance of Postgres.
- Perform
SELECT * FROM table LIMIT %vwhere the limits are: 5, 50, 100, 500, & 1000 - And scan into the following struct:
type Address struct {
Id int `json:"id" db:"pk" model:"key,auto" gorm:"column:pk;primaryKey"`
CreatedTime Time `json:"created_time" db:"created_tmz" model:"inserted" gorm:"-"`
ModifiedTime Time `json:"modified_time" db:"modified_tmz" model:"inserted,updated" gorm:"-"`
Street string `json:"street"`
City string `json:"city"`
State string `json:"state"`
Zip string `json:"zip"`
//
pushModified Time
}These results are a little more difficult to draw conclusions from. We're at the mercy of network IO and load on the database, which should have been fairly consistent throughout the benchmarks. We're also at the mercy of how Postgres stores records in memory and decides to use them for consecuitive similar requests; in other words running
a SELECT statement could easily affect the performance of the next one.
I ran all of my benchmarks multiple times and in any result below where one is doing particularly bad (or good) I very likely had a result where it landed on the other end of the spectrum.
In general I conclude that all of them perform roughly on par with each other in my simple benchmark. Certainly there are cases where one package is conclusively better than another but that is beyond the scope of my goals.
# 5 records
database/sql_5_rows-8 6807 211957 ns/op 2753 B/op 84 allocs/op
GORM_5_rows-8 6654 234121 ns/op 7934 B/op 201 allocs/op
sqlx_5_rows-8 7126 195034 ns/op 3448 B/op 92 allocs/op
scany_5_rows-8 6697 179223 ns/op 5333 B/op 188 allocs/op
sqlh_5_rows-8 6957 187767 ns/op 4406 B/op 104 allocs/op
# 50 records
database/sql_50_rows-8 3846 281356 ns/op 19434 B/op 710 allocs/op
GORM_50_rows-8 3645 389633 ns/op 36408 B/op 1418 allocs/op
sqlx_50_rows-8 2569 439411 ns/op 23174 B/op 763 allocs/op
scany_50_rows-8 2108 486062 ns/op 28727 B/op 904 allocs/op
sqlh_50_rows-8 2108 490222 ns/op 29477 B/op 865 allocs/op
# 100 records
database/sql_100_rows-8 2242 455634 ns/op 37986 B/op 1412 allocs/op
GORM_100_rows-8 2048 592872 ns/op 68158 B/op 2773 allocs/op
sqlx_100_rows-8 2461 529780 ns/op 45153 B/op 1515 allocs/op
scany_100_rows-8 2382 563152 ns/op 54625 B/op 1706 allocs/op
sqlh_100_rows-8 2518 491763 ns/op 57407 B/op 1717 allocs/op
# 500 records
database/sql_500_rows-8 1041 1302823 ns/op 191128 B/op 7669 allocs/op
GORM_500_rows-8 534 2023785 ns/op 325790 B/op 14227 allocs/op
sqlx_500_rows-8 918 1264888 ns/op 226455 B/op 8168 allocs/op
scany_500_rows-8 750 1783926 ns/op 266028 B/op 8758 allocs/op
sqlh_500_rows-8 840 1644985 ns/op 283867 B/op 9168 allocs/op
# 1,000 records
database/sql_1000_rows-8 440 2557591 ns/op 385111 B/op 15681 allocs/op
GORM_1000_rows-8 315 3682919 ns/op 650095 B/op 28736 allocs/op
sqlx_1000_rows-8 243 5090719 ns/op 454025 B/op 16677 allocs/op
scany_1000_rows-8 187 5714156 ns/op 534367 B/op 17776 allocs/op
sqlh_1000_rows-8 222 5068332 ns/op 578752 B/op 18684 allocs/opThis benchmark was performed with the same SELECT and scan destination as the Postgres SELECT benchmark.
# 5 records
database/sql_5_rows-8 12458 96676 ns/op 7320 B/op 250 allocs/op
sqlx_5_rows-8 10000 101621 ns/op 8038 B/op 258 allocs/op
scany_5_rows-8 10000 112007 ns/op 9834 B/op 354 allocs/op
sqlh_5_rows-8 10000 103653 ns/op 8990 B/op 270 allocs/op
# 50 records
database/sql_50_rows-8 3724 305367 ns/op 67448 B/op 2275 allocs/op
sqlx_50_rows-8 3951 326165 ns/op 71224 B/op 2328 allocs/op
scany_50_rows-8 3415 347603 ns/op 76601 B/op 2469 allocs/op
sqlh_50_rows-8 3453 350259 ns/op 77392 B/op 2430 allocs/op
# 100 records
database/sql_100_rows-8 2318 532861 ns/op 134089 B/op 4526 allocs/op
sqlx_100_rows-8 2119 564847 ns/op 140973 B/op 4629 allocs/op
scany_100_rows-8 2013 603275 ns/op 150671 B/op 4820 allocs/op
sqlh_100_rows-8 1963 603979 ns/op 153653 B/op 4831 allocs/op
# 500 records
database/sql_500_rows-8 501 2428738 ns/op 673477 B/op 23171 allocs/op
sqlx_500_rows-8 456 2662145 ns/op 709732 B/op 23674 allocs/op
scany_500_rows-8 438 2707386 ns/op 746132 B/op 24265 allocs/op
sqlh_500_rows-8 435 2776479 ns/op 771244 B/op 24676 allocs/op
# 1,000 records
database/sql_1000_rows-8 253 4725117 ns/op 1351002 B/op 46671 allocs/op
sqlx_1000_rows-8 228 4974677 ns/op 1423145 B/op 47674 allocs/op
scany_1000_rows-8 224 5307015 ns/op 1494309 B/op 48766 allocs/op
sqlh_1000_rows-8 222 5395924 ns/op 1544802 B/op 49676 allocs/opThe following benchmarks show iterating a set of X records and inserting them without any database transactions or prepared statements. Certainly you want to avoid this in your application if possible but there are times where it's what your application will need to do.
Results are fairly consistent across the board.
# 5 records
database/sql_insert_5_row(s)-8 220 5045438 ns/op 6789 B/op 180 allocs/op
GORM_insert_5_row(s)-8 208 6058386 ns/op 33622 B/op 471 allocs/op
squirrel_insert_5_row(s)-8 216 5424851 ns/op 28262 B/op 665 allocs/op
sqlh/model_insert_5_row(s)-8 225 6118051 ns/op 8701 B/op 205 allocs/op
# 50 records
database/sql_insert_50_row(s)-8 22 57294218 ns/op 67819 B/op 1800 allocs/op
GORM_insert_50_row(s)-8 20 62065835 ns/op 334900 B/op 4710 allocs/op
squirrel_insert_50_row(s)-8 18 56739317 ns/op 282610 B/op 6653 allocs/op
sqlh/model_insert_50_row(s)-8 21 60169900 ns/op 86988 B/op 2051 allocs/op
# 100 records
database/sql_insert_100_row(s)-8 10 117970890 ns/op 135688 B/op 3602 allocs/op
GORM_insert_100_row(s)-8 9 126497011 ns/op 671555 B/op 9427 allocs/op
squirrel_insert_100_row(s)-8 10 118073370 ns/op 564725 B/op 13301 allocs/op
sqlh/model_insert_100_row(s)-8 10 125292220 ns/op 173843 B/op 4100 allocs/op
# 500 records
database/sql_insert_500_row(s)-8 2 565426900 ns/op 677756 B/op 18003 allocs/op
GORM_insert_500_row(s)-8 2 650741850 ns/op 3347560 B/op 47080 allocs/op
squirrel_insert_500_row(s)-8 2 573679700 ns/op 2825428 B/op 66529 allocs/op
sqlh/model_insert_500_row(s)-8 2 615725850 ns/op 869668 B/op 20508 allocs/op
# 1,000 records
database/sql_insert_1000_row(s)-8 1 1163333900 ns/op 1357776 B/op 36028 allocs/op
GORM_insert_1000_row(s)-8 1 1314936200 ns/op 6693088 B/op 94130 allocs/op
squirrel_insert_1000_row(s)-8 1 1259743000 ns/op 5651088 B/op 133051 allocs/op
sqlh/model_insert_1000_row(s)-8 1 1208060600 ns/op 1739528 B/op 41015 allocs/opThe following benchmarks show Begin() -> Prepare() -> Exec() to insert a slice of X records.
# 5 records
database/sql_begin+prepare+insert_5_row(s)-8 1490 736679 ns/op 6604 B/op 165 allocs/op
GORM_slice+insert_5_row(s)-8 950 1067537 ns/op 9815 B/op 143 allocs/op
squirrel_begin+prepare+insert_5_row(s)-8 1084 1092230 ns/op 28024 B/op 645 allocs/op
sqlh/model_begin+prepare+insert_5_row(s)-8 568 2596587 ns/op 8082 B/op 196 allocs/op
# 50 records
database/sql_begin+prepare+insert_50_row(s)-8 138 8354679 ns/op 66298 B/op 1652 allocs/op
GORM_slice+insert_50_row(s)-8 501 2473041 ns/op 57312 B/op 793 allocs/op
squirrel_begin+prepare+insert_50_row(s)-8 127 11681451 ns/op 280444 B/op 6456 allocs/op
sqlh/model_begin+prepare+insert_50_row(s)-8 122 12672856 ns/op 67769 B/op 1683 allocs/op
# 100 records
database/sql_begin+prepare+insert_100_row(s)-8 70 24493961 ns/op 132531 B/op 3304 allocs/op
GORM_slice+insert_100_row(s)-8 396 2777564 ns/op 107026 B/op 1597 allocs/op
squirrel_begin+prepare+insert_100_row(s)-8 45 26156067 ns/op 560691 B/op 12910 allocs/op
sqlh/model_begin+prepare+insert_100_row(s)-8 67 23372439 ns/op 134008 B/op 3335 allocs/op
# 500 records
database/sql_begin+prepare+insert_500_row(s)-8 9 111672778 ns/op 664056 B/op 16536 allocs/op
GORM_slice+insert_500_row(s)-8 139 8918647 ns/op 583896 B/op 8009 allocs/op
squirrel_begin+prepare+insert_500_row(s)-8 13 113849262 ns/op 2802340 B/op 64551 allocs/op
sqlh/model_begin+prepare+insert_500_row(s)-8 14 89883943 ns/op 663012 B/op 16543 allocs/op
# 1,000 records
database/sql_begin+prepare+insert_1000_row(s)-8 6 176948517 ns/op 1324336 B/op 33033 allocs/op
GORM_slice+insert_1000_row(s)-8 74 16430857 ns/op 1176609 B/op 16018 allocs/op
squirrel_begin+prepare+insert_1000_row(s)-8 5 227757900 ns/op 5601816 B/op 129079 allocs/op
sqlh/model_begin+prepare+insert_1000_row(s)-8 6 195512150 ns/op 1326716 B/op 33074 allocs/opThe following benchmarks show iterating a set of X records and updating them without any database transactions or prepared statements. Certainly you want to avoid this in your application if possible but there are times where it's what your application will need to do.
Results are fairly consistent with gorm being something of an outlier:
# 5 records
database/sql_update_5_row(s)-8 482 2249577 ns/op 6537 B/op 165 allocs/op
GORM_update_5_row(s)-8 723 1735263 ns/op 29224 B/op 335 allocs/op
squirrel_update_5_row(s)-8 738 2463613 ns/op 38720 B/op 875 allocs/op
sqlh/model_update_5_row(s)-8 580 2557353 ns/op 8413 B/op 195 allocs/op
# 50 records
database/sql_update_50_row(s)-8 74 17060749 ns/op 65468 B/op 1650 allocs/op
GORM_update_50_row(s)-8 100 12066319 ns/op 292367 B/op 3352 allocs/op
squirrel_update_50_row(s)-8 62 26438821 ns/op 387376 B/op 8753 allocs/op
sqlh/model_update_50_row(s)-8 43 23284305 ns/op 84257 B/op 1950 allocs/op
# 100 records
database/sql_update_100_row(s)-8 27 46719315 ns/op 130933 B/op 3301 allocs/op
GORM_update_100_row(s)-8 61 24044793 ns/op 584659 B/op 6704 allocs/op
squirrel_update_100_row(s)-8 24 59805871 ns/op 774675 B/op 17505 allocs/op
sqlh/model_update_100_row(s)-8 24 54183550 ns/op 168450 B/op 3901 allocs/op
# 500 records
database/sql_update_500_row(s)-8 6 213189917 ns/op 658580 B/op 16997 allocs/op
GORM_update_500_row(s)-8 14 80748021 ns/op 2923198 B/op 33519 allocs/op
squirrel_update_500_row(s)-8 4 439392025 ns/op 3877772 B/op 88019 allocs/op
sqlh/model_update_500_row(s)-8 4 267054850 ns/op 844580 B/op 19752 allocs/op
# 1,000 records
database/sql_update_1000_row(s)-8 3 466049733 ns/op 1321160 B/op 34498 allocs/op
GORM_update_1000_row(s)-8 7 197242614 ns/op 5848568 B/op 67040 allocs/op
squirrel_update_1000_row(s)-8 2 779891850 ns/op 7760052 B/op 176554 allocs/op
sqlh/model_update_1000_row(s)-8 3 382446033 ns/op 1690760 B/op 39752 allocs/opThe following benchmarks show Begin() -> Prepare() -> Exec() to insert a slice of X records.
# 5 records
database/sql_begin+prepare+update_5_row(s)-8 1110 1336426 ns/op 6895 B/op 150 allocs/op
GORM_update_5_row(s)-8 3848 520668 ns/op 14241 B/op 162 allocs/op
squirrel_begin+prepare+update_5_row(s)-8 841 1529204 ns/op 38957 B/op 855 allocs/op
sqlh/model_begin+prepare+update_5_row(s)-8 649 2008840 ns/op 7885 B/op 173 allocs/op
# 50 records
database/sql_begin+prepare+update_50_row(s)-8 100 10373155 ns/op 69153 B/op 1501 allocs/op
GORM_update_50_row(s)-8 535 7558777 ns/op 110557 B/op 820 allocs/op
squirrel_begin+prepare+update_50_row(s)-8 81 17105143 ns/op 389943 B/op 8553 allocs/op
sqlh/model_begin+prepare+update_50_row(s)-8 97 17899106 ns/op 70424 B/op 1568 allocs/op
# 100 records
database/sql_begin+prepare+update_100_row(s)-8 63 19669398 ns/op 138172 B/op 3001 allocs/op
GORM_update_100_row(s)-8 280 10390849 ns/op 205307 B/op 1625 allocs/op
squirrel_begin+prepare+update_100_row(s)-8 36 28659156 ns/op 779430 B/op 17104 allocs/op
sqlh/model_begin+prepare+update_100_row(s)-8 64 21718161 ns/op 139811 B/op 3119 allocs/op
# 500 records
database/sql_begin+prepare+update_500_row(s)-8 12 97196517 ns/op 695215 B/op 15498 allocs/op
GORM_update_500_row(s)-8 74 21223735 ns/op 1006385 B/op 8681 allocs/op
squirrel_begin+prepare+update_500_row(s)-8 10 123098130 ns/op 3903352 B/op 86021 allocs/op
sqlh/model_begin+prepare+update_500_row(s)-8 10 135324480 ns/op 697669 B/op 15767 allocs/op
# 1,000 records
database/sql_begin+prepare+update_1000_row(s)-8 7 206369114 ns/op 1396044 B/op 31509 allocs/op
GORM_update_1000_row(s)-8 39 38828905 ns/op 2207693 B/op 17690 allocs/op
squirrel_begin+prepare+update_1000_row(s)-8 6 269227417 ns/op 7809578 B/op 172543 allocs/op
sqlh/model_begin+prepare+update_1000_row(s)-8 6 229407333 ns/op 1397428 B/op 31773 allocs/opThe previous Postgres tests are now repeated with Sqlite sans gorm.
# 5 records
database/sql_insert_5_row(s)-8 45 29689611 ns/op 266493 B/op 6923 allocs/op
squirrel_insert_5_row(s)-8 50 25831794 ns/op 288350 B/op 7454 allocs/op
sqlh/model_insert_5_row(s)-8 51 31900388 ns/op 268402 B/op 6955 allocs/op
# 50 records
database/sql_insert_50_row(s)-8 4 257990950 ns/op 2665130 B/op 69301 allocs/op
squirrel_insert_50_row(s)-8 4 264287750 ns/op 2883536 B/op 74554 allocs/op
sqlh/model_insert_50_row(s)-8 4 381673525 ns/op 2684044 B/op 69550 allocs/op
# 100 records
database/sql_insert_100_row(s)-8 2 515282400 ns/op 5330480 B/op 138605 allocs/op
squirrel_insert_100_row(s)-8 2 514017900 ns/op 5766700 B/op 149104 allocs/op
sqlh/model_insert_100_row(s)-8 2 779631350 ns/op 5368056 B/op 139100 allocs/op
# 500 records
database/sql_insert_500_row(s)-8 1 2612650600 ns/op 26649912 B/op 693013 allocs/op
squirrel_insert_500_row(s)-8 1 3168402800 ns/op 28837584 B/op 745552 allocs/op
sqlh/model_insert_500_row(s)-8 1 2637685200 ns/op 26840328 B/op 695505 allocs/op
# 1,000 records
database/sql_insert_1000_row(s)-8 1 5907092800 ns/op 53297856 B/op 1386017 allocs/op
squirrel_insert_1000_row(s)-8 1 5839871100 ns/op 57670072 B/op 1491095 allocs/op
sqlh/model_insert_1000_row(s)-8 1 5444616300 ns/op 53682080 B/op 1391011 allocs/op# 5 records
database/sql_begin+prepare+insert_5_row(s)-8 1992 595825 ns/op 269003 B/op 6975 allocs/op
squirrel_begin+prepare+insert_5_row(s)-8 1833 623820 ns/op 290786 B/op 7495 allocs/op
sqlh/model_begin+prepare+insert_5_row(s)-8 208 5671543 ns/op 269702 B/op 6987 allocs/op
# 50 records
database/sql_begin+prepare+insert_50_row(s)-8 214 6060468 ns/op 2690042 B/op 69754 allocs/op
squirrel_begin+prepare+insert_50_row(s)-8 192 6271936 ns/op 2907824 B/op 74958 allocs/op
sqlh/model_begin+prepare+insert_50_row(s)-8 100 10821204 ns/op 2690489 B/op 69763 allocs/op
# 100 records
database/sql_begin+prepare+insert_100_row(s)-8 106 11184752 ns/op 5379689 B/op 139505 allocs/op
squirrel_begin+prepare+insert_100_row(s)-8 96 12460612 ns/op 5815093 B/op 149910 allocs/op
sqlh/model_begin+prepare+insert_100_row(s)-8 76 16489736 ns/op 5380870 B/op 139521 allocs/op
# 500 records
database/sql_begin+prepare+insert_500_row(s)-8 19 57751174 ns/op 26901126 B/op 697553 allocs/op
squirrel_begin+prepare+insert_500_row(s)-8 18 62421122 ns/op 29076555 B/op 749562 allocs/op
sqlh/model_begin+prepare+insert_500_row(s)-8 18 61375433 ns/op 26900149 B/op 697547 allocs/op
# 1,000 records
database/sql_begin+prepare+insert_1000_row(s)-8 9 111906267 ns/op 53799579 B/op 1395079 allocs/op
squirrel_begin+prepare+insert_1000_row(s)-8 8 125255625 ns/op 58156813 B/op 1499166 allocs/op
sqlh/model_begin+prepare+insert_1000_row(s)-8 9 120388589 ns/op 53796854 B/op 1395054 allocs/op# 5 records
database/sql_update_5_row(s)-8 10000 123116 ns/op 4610 B/op 175 allocs/op
squirrel_update_5_row(s)-8 5836 213105 ns/op 37144 B/op 935 allocs/op
sqlh/model_update_5_row(s)-8 8781 131921 ns/op 6524 B/op 205 allocs/op
# 50 records
database/sql_update_50_row(s)-8 988 1238107 ns/op 46097 B/op 1751 allocs/op
squirrel_update_50_row(s)-8 570 2128517 ns/op 371435 B/op 9352 allocs/op
sqlh/model_update_50_row(s)-8 906 1331060 ns/op 65286 B/op 2050 allocs/op
# 100 records
database/sql_update_100_row(s)-8 483 2446387 ns/op 92150 B/op 3501 allocs/op
squirrel_update_100_row(s)-8 279 4267277 ns/op 742911 B/op 18704 allocs/op
sqlh/model_update_100_row(s)-8 457 2667099 ns/op 130623 B/op 4102 allocs/op
# 500 records
database/sql_update_500_row(s)-8 97 12766361 ns/op 466980 B/op 18001 allocs/op
squirrel_update_500_row(s)-8 55 21336253 ns/op 3722212 B/op 94011 allocs/op
sqlh/model_update_500_row(s)-8 90 13257092 ns/op 654745 B/op 20753 allocs/op
# 1,000 records
database/sql_update_1000_row(s)-8 49 24498727 ns/op 939114 B/op 36502 allocs/op
squirrel_update_1000_row(s)-8 27 42796267 ns/op 7453046 B/op 188537 allocs/op
sqlh/model_update_1000_row(s)-8 44 26776673 ns/op 1312121 B/op 41767 allocs/op# 5 records
database/sql_begin+prepare+update_5_row(s)-8 9703 130129 ns/op 5847 B/op 190 allocs/op
squirrel_begin+prepare+update_5_row(s)-8 5458 218285 ns/op 38304 B/op 945 allocs/op
sqlh/model_begin+prepare+update_5_row(s)-8 8781 136517 ns/op 6591 B/op 205 allocs/op
# 50 records
database/sql_begin+prepare+update_50_row(s)-8 916 1297656 ns/op 58457 B/op 1900 allocs/op
squirrel_begin+prepare+update_50_row(s)-8 550 2339813 ns/op 383147 B/op 9453 allocs/op
sqlh/model_begin+prepare+update_50_row(s)-8 859 1350686 ns/op 59912 B/op 1960 allocs/op
# 100 records
database/sql_begin+prepare+update_100_row(s)-8 462 2594040 ns/op 116932 B/op 3801 allocs/op
squirrel_begin+prepare+update_100_row(s)-8 277 4367517 ns/op 766107 B/op 18904 allocs/op
sqlh/model_begin+prepare+update_100_row(s)-8 440 2738170 ns/op 119264 B/op 3912 allocs/op
# 500 records
database/sql_begin+prepare+update_500_row(s)-8 91 12915989 ns/op 590369 B/op 19494 allocs/op
squirrel_begin+prepare+update_500_row(s)-8 55 21805969 ns/op 3837766 B/op 95006 allocs/op
sqlh/model_begin+prepare+update_500_row(s)-8 87 13552601 ns/op 595252 B/op 19761 allocs/op
# 1,000 records
database/sql_begin+prepare+update_1000_row(s)-8 45 25837742 ns/op 1186918 B/op 39500 allocs/op
squirrel_begin+prepare+update_1000_row(s)-8 26 43744408 ns/op 7684063 B/op 190526 allocs/op
sqlh/model_begin+prepare+update_1000_row(s)-8 43 27197272 ns/op 1192095 B/op 39770 allocs/op