Neues inOpen-Source-SQL-Datenbanken

@MarkusWinand • @ModernSQL

http://www.almaden.ibm.com/cs/people/chamberlin/sequel-1974.pdf

Neues inOpen-Source-SQL-Datenbanken

@MarkusWinand • @ModernSQL

http://www.almaden.ibm.com/cs/people/chamberlin/sequel-1974.pdf

SQL-92

CHECKConstraints

CHECK Constraints Since SQL-92CREATETABLEorder_lines(…qtyINTEGERNOTNULLCHECK(qty>0),…)

CHECK Constraints Since SQL-92CREATETABLEorder_lines(…qtyINTEGERNOTNULLCHECK(qty>0),…)

INSERT…(…,qty,…)VALUES(…,1,…)

CHECK Constraints Since SQL-92CREATETABLEorder_lines(…qtyINTEGERNOTNULLCHECK(qty>0),…)

INSERT…(…,qty,…)VALUES(…,1,…)INSERT…(…,qty,…)VALUES(…,3,…)

CHECK Constraints Since SQL-92CREATETABLEorder_lines(…qtyINTEGERNOTNULLCHECK(qty>0),…)

INSERT…(…,qty,…)VALUES(…,1,…)INSERT…(…,qty,…)VALUES(…,3,…)INSERT…(…,qty,…)VALUES(…,0,…)

CHECK Constraints Since SQL-92CREATETABLEorder_lines(…qtyINTEGERNOTNULLCHECK(qty>0),…)

INSERT…(…,qty,…)VALUES(…,1,…)INSERT…(…,qty,…)VALUES(…,3,…)INSERT…(…,qty,…)VALUES(…,0,…)

Before MySQL 8.0.16and MariaDB 10.2:

Syntax accepted,Constraint ignored

CHECK Constraints Since SQL-921999

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10.2 MariaDB8.0.16 MySQL

8.3 PostgreSQL3.5.7 SQLite

9.7 DB2 LUW11gR1 Oracle

2008R2 SQL Server

INTERSECT and EXCEPT

Since SQL-92INTERSECT & EXCEPT

UNION[ALL]

Concatenatestwo results

Since SQL-92INTERSECT & EXCEPT

UNION[ALL]

Concatenatestwo results

INTERSECT[ALL]

Common rows from two results

Since SQL-92INTERSECT & EXCEPT

UNION[ALL]

Concatenatestwo results

INTERSECT[ALL]

Common rows from two results

EXCEPT[ALL]

Remove rowsfrom first result

INTERSECT & EXCEPT Since SQL-921999

2001

2003

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10.3[0] MariaDBMySQL

8.3 PostgreSQL3.5.7[0] SQLite

9.7 DB2 LUW11gR1[0] Oracle

2008R2[0] SQL Server[0]Not [all]

SQL:1999

LATERAL

Select-list sub-queries must be scalar[0]:

LATERAL Before SQL:1999

SELECT…,(SELECTcolumn_1FROMt1WHEREt1.x=t2.y)AScFROMt2…

(an atomic quantity that can hold only one value at a time[1])

[0] Neglecting row values and other workarounds here; [1] https://en.wikipedia.org/wiki/Scalar

Select-list sub-queries must be scalar[0]:

LATERAL Before SQL:1999

SELECT…,(SELECTcolumn_1FROMt1WHEREt1.x=t2.y)AScFROMt2…

(an atomic quantity that can hold only one value at a time[1])

[0] Neglecting row values and other workarounds here; [1] https://en.wikipedia.org/wiki/Scalar

✗,column_2

More thanone column? ⇒Syntax error

Select-list sub-queries must be scalar[0]:

LATERAL Before SQL:1999

SELECT…,(SELECTcolumn_1FROMt1WHEREt1.x=t2.y)AScFROMt2…

(an atomic quantity that can hold only one value at a time[1])

[0] Neglecting row values and other workarounds here; [1] https://en.wikipedia.org/wiki/Scalar

✗,column_2

More thanone column? ⇒Syntax error

}More thanone row?

⇒Runtime error!

SELECT*FROMt1CROSSJOINLATERAL(SELECT*FROMt2WHEREt2.x=t1.x)derived_tableON(true)

LATERAL Since SQL:1999Lateral derived queries can see table names defined before:

SELECT*FROMt1CROSSJOINLATERAL(SELECT*FROMt2WHEREt2.x=t1.x)derived_tableON(true)

LATERAL Since SQL:1999

Valid due to

LATERAL

keyword

Lateral derived queries can see table names defined before:

SELECT*FROMt1CROSSJOINLATERAL(SELECT*FROMt2WHEREt2.x=t1.x)derived_tableON(true)

LATERAL Since SQL:1999

Valid due to

LATERAL

keyword

Useless, but still required

Lateral derived queries can see table names defined before:

SELECT*FROMt1CROSSJOINLATERAL(SELECT*FROMt2WHEREt2.x=t1.x)derived_tableON(true)

LATERAL Since SQL:1999

Valid due to

LATERAL

keyword

Lateral derived queries can see table names defined before:

Use CROSS JOIN to omit the ON clause

But WHY?

Use-CasesLATERAL

‣ Top-N per group

inside a lateral derived tableFETCHFIRST (or LIMIT, TOP)applies per row from left tables.

Use-CasesLATERAL

FROMtJOINLATERAL(SELECT…FROM…WHEREt.c=…ORDERBY…LIMIT10)derived_table

‣ Top-N per group

inside a lateral derived tableFETCHFIRST (or LIMIT, TOP)applies per row from left tables.

Use-CasesLATERAL

FROMtJOINLATERAL(SELECT…FROM…WHEREt.c=…ORDERBY…LIMIT10)derived_table

‣ Top-N per group

inside a lateral derived tableFETCHFIRST (or LIMIT, TOP)applies per row from left tables.

Use-CasesLATERAL

Add proper indexfor Top-N query

http://use-the-index-luke.com/sql/partial-results/top-n-queries

FROMtJOINLATERAL(SELECT…FROM…WHEREt.c=…ORDERBY…LIMIT10)derived_table

‣ Top-N per group

inside a lateral derived tableFETCHFIRST (or LIMIT, TOP)applies per row from left tables.

‣ Also useful to find most recent news from several subscribed topics (“multi-source top-N”).

Use-CasesLATERAL

Add proper indexfor Top-N query

http://use-the-index-luke.com/sql/partial-results/top-n-queries

FROMtJOINLATERAL(SELECT…FROM…WHEREt.c=…ORDERBY…LIMIT10)derived_table

‣ Top-N per group

inside a lateral derived tableFETCHFIRST (or LIMIT, TOP)applies per row from left tables.

‣ Also useful to find most recent news from several subscribed topics (“multi-source top-N”).

‣ Table function arguments

(TABLE often implies LATERAL)

Use-CasesLATERAL

FROMtJOINTABLE(your_func(t.c))

LATERAL is the "for each" loop of SQL

LATERAL plays well with outer and cross joins

LATERAL is great for Top-N subqueries

LATERAL can join table functions (unnest!)

LATERAL In a Nutshell

LATERAL Availability1999

2001

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2017

5.1 MariaDB8.0.14 MySQL

9.3 PostgreSQLSQLite

9.1 DB2 LUW11gR1[0] 12cR1 Oracle

2005[1] SQL Server[0]Undocumented. Requires setting trace event 22829.[1]LATERAL is not supported as of SQL Server 2016 but [CROSS|OUTER]APPLY can be used for the same effect.

SQL:2003

BOOLEANTests

Before we start

SQL uses a three-valued logic. Boolean values are either

true, false or unknown(=null).

See: http://modern-sql.com/concept/three-valued-logic

BOOLEANAggregates

BOOLEANTests

Similar to isnull, there are tests for each Boolean value(of which there are three: true, false, unknown/null)

IS[NOT][TRUE|FALSE|UNKNOWN]

Since SQL:2003

CREATETABLEprices(…valid_fromDATENOTNULL,valid_toDATE,--null:openend…CHECK(valid_from<valid_to),);

WHEREvalid_from<CURRENT_DATEAND(valid_to<=CURRENT_DATE)ISNOTFALSE

BOOLEANTests Since SQL:2003

CREATETABLEprices(…valid_fromDATENOTNULL,valid_toDATE,--null:openend…CHECK(valid_from<valid_to),);

WHEREvalid_from<CURRENT_DATEAND(valid_to<=CURRENT_DATE)ISNOTFALSE

BOOLEANTests Since SQL:2003

CREATETABLEprices(…valid_fromDATENOTNULL,valid_toDATE,--null:openend…CHECK(valid_from<valid_to),);

WHEREvalid_from<CURRENT_DATEAND(valid_to<=CURRENT_DATE)ISNOTFALSE

BOOLEANTests Since SQL:2003

UNKNOWN ifVALID_TO is NULL

CREATETABLEprices(…valid_fromDATENOTNULL,valid_toDATE,--null:openend…CHECK(valid_from<valid_to),);

WHEREvalid_from<CURRENT_DATEAND(valid_to<=CURRENT_DATE)ISNOTFALSE

BOOLEANTests Since SQL:2003

UNKNOWN ifVALID_TO is NULL Takes TRUE and

UNKNOWN

BOOLEANTests Since SQL:20031999

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5.1 MariaDB5.0.51a MySQL8.3 PostgreSQL

3.23.0[0] SQLite

DB2 LUWOracleSQL Server

[0]No IS [NOT] UNKNOWN. Use IS [NOT] NULL instead.

BOOLEANType

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

Without NOT NULLit is a

three-valued Boolean

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

SELECT…FROM…WHERENOT(deleted)

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

Alias for int

MySQL MariaDBSQLite

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

Alias for int

MySQL MariaDBSQLite

INSERT…(…,deleted,…)VALUES(…,true,…)

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

Alias for int

MySQL MariaDBSQLite

INSERT…(…,deleted,…)VALUES(…,true,…)INSERT…(…,deleted,…)VALUES(…,false,…)

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

Alias for int

MySQL MariaDBSQLite

INSERT…(…,deleted,…)VALUES(…,true,…)INSERT…(…,deleted,…)VALUES(…,false,…)INSERT…(…,deleted,…)VALUES(…,42,…)

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

Alias for int

MySQL MariaDBSQLite

INSERT…(…,deleted,…)VALUES(…,true,…)INSERT…(…,deleted,…)VALUES(…,false,…)INSERT…(…,deleted,…)VALUES(…,42,…)

UNIQUE,

BOOLEANTypeCREATETABLE…(…deletedBOOLEANNOTNULL,…)

Since SQL:2003

Alias for int

MySQL MariaDBSQLite

INSERT…(…,deleted,…)VALUES(…,true,…)INSERT…(…,deleted,…)VALUES(…,false,…)INSERT…(…,deleted,…)VALUES(…,42,…)

UNIQUE,

+----+|de|+----+|1||0||42|+----+

BOOLEANType Since SQL:2003

Note that boolean in base tables is often questionable:

BOOLEANType Since SQL:2003

Note that boolean in base tables is often questionable:

‣deleted flags are a poor mans temporal database model

BOOLEANType Since SQL:2003

Note that boolean in base tables is often questionable:

‣deleted flags are a poor mans temporal database model

‣States often need more than two (or three) values consider using an enum instead (can be evolved)

BOOLEANType Since SQL:2003

Note that boolean in base tables is often questionable:

‣deleted flags are a poor mans temporal database model

‣States often need more than two (or three) values consider using an enum instead (can be evolved)See: 3 Reasons I Hate Booleans In Databases by Jeff Potterhttps://medium.com/@jpotts18/646d99696580

BOOLEANType Since SQL:20031999

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5.1[0] MariaDB5.0.51a[0] MySQL

8.4 PostgreSQL3.23.0[0] SQLite

DB2 LUWOracleSQL Server

[0]BOOLEAN, TRUE, FALSE are aliases for TINYINT(1), 1, 0 respectivley.

OVERand

PARTITIONBY

OVER (PARTITION BY) The ProblemTwo distinct concepts could not be used independently:

OVER (PARTITION BY) The ProblemTwo distinct concepts could not be used independently:

‣Merge rows with the same key properties

‣ GROUPBY to specify key properties

‣ DISTINCT to use full row as key

OVER (PARTITION BY) The ProblemTwo distinct concepts could not be used independently:

‣Merge rows with the same key properties

‣ GROUPBY to specify key properties

‣ DISTINCT to use full row as key

‣ Aggregate data from related rows ‣ Requires GROUPBY to segregate the rows

‣ COUNT, SUM, AVG, MIN, MAX to aggregate grouped rows

OVER (PARTITION BY) The Problem

OVER (PARTITION BY) The Problem

SELECTc1,c2FROMt

SELECTc1,c2FROMt

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No SELECTc1

,c2FROMt

SELECTc1,c2FROMt

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No SELECTc1

,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMt

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMt

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMt

SELECTc1,SUM(c2)totFROMtGROUPBYc1

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMt

SELECTc1,SUM(c2)totFROMtGROUPBYc1

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMtJOIN()taON(t.c1=ta.c1)

SELECTc1,SUM(c2)totFROMtGROUPBYc1

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMtJOIN()taON(t.c1=ta.c1)

SELECTc1,SUM(c2)totFROMtGROUPBYc1

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMtJOIN()taON(t.c1=ta.c1)

SELECTc1,SUM(c2)totFROMtGROUPBYc1

,tot

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) The Problem

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMtJOIN()taON(t.c1=ta.c1)

SELECTc1,SUM(c2)totFROMtGROUPBYc1

,tot

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) Since SQL:2003

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMtFROMt

SELECTc1,SUM(c2)totFROMtGROUPBYc1

OVER (PARTITION BY) Since SQL:2003

Yes ⇠

Mer

ge ro

ws ⇢

No

No ⇠ Aggregate ⇢ Yes

SELECTc1,c2FROMt

SELECTDISTINCTc1,c2FROMt

SELECTc1,c2FROMt

FROMt

,SUM(c2)OVER(PARTITIONBYc1)

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 600022 1000 600022 1000 6000333 1000 6000333 1000 6000333 1000 6000

OVER (PARTITION BY) How it works

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 600022 1000 600022 1000 6000333 1000 6000333 1000 6000333 1000 6000

OVER (PARTITION BY) How it works

Look here

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 600022 1000 600022 1000 6000333 1000 6000333 1000 6000333 1000 6000

OVER (PARTITION BY) How it works

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 600022 1000 600022 1000 6000333 1000 6000333 1000 6000333 1000 6000

OVER (PARTITION BY) How it works

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 600022 1000 600022 1000 6000333 1000 6000333 1000 6000333 1000 6000

OVER (PARTITION BY) How it works

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 600022 1000 600022 1000 6000333 1000 6000333 1000 6000333 1000 6000

OVER (PARTITION BY) How it works

dep salary1 1000 600022 1000 600022 1000 6000333 1000 6000333 1000 6000333 1000 6000

SELECTdep,salary,SUM(salary)OVER()FROMemp

OVER (PARTITION BY) How it works

)

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 100022 1000 200022 1000 2000333 1000 3000333 1000 3000333 1000 3000

OVER (PARTITION BY) How it works

)

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 100022 1000 200022 1000 2000333 1000 3000333 1000 3000333 1000 3000

OVER (PARTITION BY) How it works

)PARTITIONBYdep

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 100022 1000 200022 1000 2000333 1000 3000333 1000 3000333 1000 3000

OVER (PARTITION BY) How it works

)PARTITIONBYdep

SELECTdep,salary,SUM(salary)OVER()FROMemp

dep salary1 1000 100022 1000 200022 1000 2000333 1000 3000333 1000 3000333 1000 3000

OVER (PARTITION BY) How it works

)PARTITIONBYdep

OVERand

ORDERBY(Framing & Ranking)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) The Problem

SELECTid,value,FROMtransactionst

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) The Problem

SELECTid,value,FROMtransactionst

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) The Problem

SELECTid,value,FROMtransactionst

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) The Problem

SELECTid,value,

(SELECTSUM(value)FROMtransactionst2WHEREt2.id<=t.id)

FROMtransactionst

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) The Problem

SELECTid,value,

(SELECTSUM(value)FROMtransactionst2WHEREt2.id<=t.id)

FROMtransactionst

Range segregation (<=)not possible with

GROUP BY orPARTITION BY

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

(SELECTSUM(value)FROMtransactionst2WHEREt2.id<=t.id)

FROMtransactionst

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYid

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDING

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +30

22 3 -10 +20

333 4 +50 +70

333 5 -30 +40

333 6 -20 +20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10

22 2 +20

22 3 -10

333 4 +50

333 5 -30

333 6 -20

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

OVER (ORDER BY) Since SQL:2003

SELECTid,value,

FROMtransactionst

SUM(value)OVER(

)

acnt id value balance

1 1 +10 +10

22 2 +20 +20

22 3 -10 +10

333 4 +50 +50

333 5 -30 +20

333 6 -20 .0

ORDERBYidROWSBETWEENUNBOUNDEDPRECEDINGANDCURRENTROW

PARTITIONBYacnt

‣ Aggregates without GROUPBY

Use CasesOVER (SQL:2003)

‣ Aggregates without GROUPBY

‣ Running totals, moving averages

Use Cases

AVG(…)OVER(ORDERBY…ROWSBETWEEN3PRECEDINGAND3FOLLOWING)moving_avg

OVER (SQL:2003)

‣ Aggregates without GROUPBY

‣ Running totals, moving averages

‣ Ranking

Use Cases

AVG(…)OVER(ORDERBY…ROWSBETWEEN3PRECEDINGAND3FOLLOWING)moving_avg

OVER (SQL:2003)

‣ Aggregates without GROUPBY

‣ Running totals, moving averages

‣ Ranking‣ Top-N per Group

Use Cases

SELECT*FROM(SELECTROW_NUMBER()OVER(PARTITIONBY…ORDERBY…)rn,t.*FROMt)numbered_tWHERErn<=3

AVG(…)OVER(ORDERBY…ROWSBETWEEN3PRECEDINGAND3FOLLOWING)moving_avg

OVER (SQL:2003)

‣ Aggregates without GROUPBY

‣ Running totals, moving averages

‣ Ranking‣ Top-N per Group

‣ Avoiding self-joins

Use Cases

SELECT*FROM(SELECTROW_NUMBER()OVER(PARTITIONBY…ORDERBY…)rn,t.*FROMt)numbered_tWHERErn<=3

AVG(…)OVER(ORDERBY…ROWSBETWEEN3PRECEDINGAND3FOLLOWING)moving_avg

OVER (SQL:2003)

‣ Aggregates without GROUPBY

‣ Running totals, moving averages

‣ Ranking‣ Top-N per Group

‣ Avoiding self-joins

[… many more …]

Use Cases

SELECT*FROM(SELECTROW_NUMBER()OVER(PARTITIONBY…ORDERBY…)rn,t.*FROMt)numbered_tWHERErn<=3

AVG(…)OVER(ORDERBY…ROWSBETWEEN3PRECEDINGAND3FOLLOWING)moving_avg

OVER (SQL:2003)

1999

2001

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2005

2007

2009

2011

2013

2015

2017

5.1 10.2 MariaDB8.0 MySQL

8.4 PostgreSQL3.25.0 SQLite

7.0 DB2 LUW8i Oracle

2005[0] 2012 SQL Server[0]No framing

OVER (SQL:2003) Availability

1999

2001

2003

2005

2007

2009

2011

2013

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2017

5.1 10.2 MariaDB8.0 MySQL

8.4 PostgreSQL3.25.0 SQLite

7.0 DB2 LUW8i Oracle

2005[0] 2012 SQL Server[0]No framing

OVER (SQL:2003) AvailabilityImpalaSpark

NuoDB

BigQuery Hive

OVERSQL:2003 frame exclusion

Since SQL:2003OVER(ORDERBY…BETWEEN…exclude[noothers|currentrow|group|ties])

OVER (frame exclusion)

Since SQL:2003OVER(ORDERBY…BETWEEN…exclude[noothers|currentrow|group|ties])

default

OVER (frame exclusion)

noothers

Since SQL:2003

x12223

OVER(ORDERBY…BETWEEN…exclude[noothers|currentrow|group|ties])

default

OVER (frame exclusion)

noothers

currentrow

Since SQL:2003

x12223

OVER(ORDERBY…BETWEEN…exclude[noothers|currentrow|group|ties])

default

OVER (frame exclusion)

currentrow

groupx=current_row

currentrow

Since SQL:2003

x12223

OVER(ORDERBY…BETWEEN…exclude[noothers|currentrow|group|ties])

default

OVER (frame exclusion)

group

tiesgroupx=current_row

currentrow

Since SQL:2003

x12223

OVER(ORDERBY…BETWEEN…exclude[noothers|currentrow|group|ties])

default

OVER (frame exclusion)

ties

OVER (frame exclusion) Since SQL:20111999

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11 PostgreSQL3.28.0 SQLite

DB2 LUWOracleSQL Server

FILTER

FILTER Before we start

In SQL, most aggregate functions* drop null arguments

prior to the aggregation.

*Exceptions: Some aggregate functions that return structured data: array_agg, json_objectagg, xmlagg

See: http://modern-sql.com/concept/null#aggregates

SELECTYEAR,SUM(CASEWHENMONTH=1THENrevenueELSE0END)JAN,SUM(CASEWHENMONTH=2THENrevenueEND)FEB,…FROMsalesGROUPBYYEAR

FILTER The ProblemPivot table: Years on the Y axis, month on X:

SELECTYEAR,SUM(CASEWHENMONTH=1THENrevenueELSE0END)JAN,SUM(CASEWHENMONTH=2THENrevenueEND)FEB,…FROMsalesGROUPBYYEAR

FILTER The ProblemPivot table: Years on the Y axis, month on X:

SELECTYEAR,SUM(CASEWHENMONTH=1THENrevenueELSE0END)JAN,SUM(CASEWHENMONTH=2THENrevenueEND)FEB,…FROMsalesGROUPBYYEAR

FILTER The ProblemPivot table: Years on the Y axis, month on X:

SELECTYEAR,SUM(CASEWHENMONTH=1THENrevenueELSE0END)JAN,SUM(CASEWHENMONTH=2THENrevenueEND)FEB,…FROMsalesGROUPBYYEAR

FILTER The ProblemPivot table: Years on the Y axis, month on X:

Optional:ELSE NULL is default

SELECTYEAR,SUM(CASEWHENMONTH=1THENrevenueELSE0END)JAN,SUM(CASEWHENMONTH=2THENrevenueEND)FEB,…FROMsalesGROUPBYYEAR

FILTER The ProblemPivot table: Years on the Y axis, month on X:

Optional:ELSE NULL is default

Aggregatesignore NULL*

*Exceptions:array_agg, json_objectagg, xmlagg See: https://modern-sql.com/concept/null#aggregates

SELECTYEAR,SUM(CASEWHENMONTH=1THENrevenueELSE0END)JAN,SUM(CASEWHENMONTH=2THENrevenueEND)FEB,…FROMsalesGROUPBYYEAR

FILTER The ProblemPivot table: Years on the Y axis, month on X:

SELECTYEAR,SUM(revenue)FILTER(WHEREMONTH=1)JAN,SUM(revenue)FILTER(WHEREMONTH=2)FEB,…FROMsalesGROUPBYYEAR;

FILTER Since SQL:2003SQL:2003 allows FILTER(WHERE…) after aggregates:

FILTER Since SQL:2003

Year

2016

2016

2016

2016

2016

Month

1

2

3

...

12

Revenue

1

23

345

...

1234

Year

2016

Jan

1

Feb

23

Mar

345

...

...

Dec

1234

SUM(…) F

ILTE

R(WHERE …)

SUM(…) F

ILTER(WHERE

month=2)

SUM(revenu

e) FIL

TER(WHERE

month=3)

SUM(reven

ue) FI

LTER(WHERE mo

nth=…)

SUM(reven

ue) FIL

TER(WH

ERE month=

12)

Pivot in SQL1. Use GROUP BY

to combine rows2. Use FILTER to pick

rows per column

See: https://modern-sql.com/use-case/pivot

FILTER Availability1999

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DB2 LUWOracleSQL Server

[0]Only with OVER clause

Inverse Distribution Functions (percentiles)

Inverse Distribution Functions The ProblemGrouped rows cannot be ordered prior to aggregation.

(how to get the middle value (median) of a set)

SELECTd1.valFROMdatad1JOINdatad2ON(d1.val<d2.valOR(d1.val=d2.valANDd1.id<d2.id))GROUPBYd1.valHAVINGcount(*)=(SELECTFLOOR(COUNT(*)/2)FROMdatad3)

Inverse Distribution Functions The ProblemGrouped rows cannot be ordered prior to aggregation.

(how to get the middle value (median) of a set)

SELECTd1.valFROMdatad1JOINdatad2ON(d1.val<d2.valOR(d1.val=d2.valANDd1.id<d2.id))GROUPBYd1.valHAVINGcount(*)=(SELECTFLOOR(COUNT(*)/2)FROMdatad3)

Inverse Distribution Functions The ProblemGrouped rows cannot be ordered prior to aggregation.

(how to get the middle value (median) of a set)

Number rows

SELECTd1.valFROMdatad1JOINdatad2ON(d1.val<d2.valOR(d1.val=d2.valANDd1.id<d2.id))GROUPBYd1.valHAVINGcount(*)=(SELECTFLOOR(COUNT(*)/2)FROMdatad3)

Inverse Distribution Functions The ProblemGrouped rows cannot be ordered prior to aggregation.

(how to get the middle value (median) of a set)

Number rows

Pick middle one

SELECTd1.valFROMdatad1JOINdatad2ON(d1.val<d2.valOR(d1.val=d2.valANDd1.id<d2.id))GROUPBYd1.valHAVINGcount(*)=(SELECTFLOOR(COUNT(*)/2)FROMdatad3)

Inverse Distribution Functions The ProblemGrouped rows cannot be ordered prior to aggregation.

(how to get the middle value (median) of a set)

Number rows

Pick middle one

SELECTd1.valFROMdatad1JOINdatad2ON(d1.val<d2.valOR(d1.val=d2.valANDd1.id<d2.id))GROUPBYd1.valHAVINGcount(*)=(SELECTFLOOR(COUNT(*)/2)FROMdatad3)

Inverse Distribution Functions The ProblemGrouped rows cannot be ordered prior to aggregation.

(how to get the middle value (median) of a set)

Number rows

Pick middle one

Since SQL:2003Inverse Distribution Functions

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Median

Since SQL:2003Inverse Distribution Functions

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Median

Which value?

Since SQL:2003Inverse Distribution Functions

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

1

2

3

4

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

1

2

3

4

0 0.25 0.5 0.75 11

2

3

4

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

1

2

3

4

0 0.25 0.5 0.75 11

2

3

4

0 0.25 0.5 0.75 11

2

3

4

PERCENTILE_DISC

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

1

2

3

4

0 0.25 0.5 0.75 11

2

3

4

0 0.25 0.5 0.75 11

2

3

4

PERCENTILE_DISC0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_DISC

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

1

2

3

4

0 0.25 0.5 0.75 11

2

3

4

0 0.25 0.5 0.75 11

2

3

4

PERCENTILE_DISC0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_DISC0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_DISC(0.5)

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

1

2

3

4

0 0.25 0.5 0.75 11

2

3

4

0 0.25 0.5 0.75 11

2

3

4

PERCENTILE_DISC0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_DISC0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_DISC(0.5)0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_CONT

PERCENTILE_DISC(0.5)

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

1

2

3

4

0 0.25 0.5 0.75 11

2

3

4

0 0.25 0.5 0.75 11

2

3

4

PERCENTILE_DISC0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_DISC0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_DISC(0.5)0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_CONT

PERCENTILE_DISC(0.5)0 0.25 0.5 0.75 1

1

2

3

4

PERCENTILE_CONT(0.5)

PERCENTILE_DISC(0.5)

SELECTPERCENTILE_DISC(0.5)WITHINGROUP(ORDERBYval)FROMdata

Since SQL:2003Inverse Distribution Functions

Two variants: ‣ for discrete values (categories) ‣ for continuous values (linear interpolation)

Inverse Distribution Functions Availability1999

2001

2003

2005

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2009

2011

2013

2015

2017

5.1 10.3[0] MariaDBMySQL

9.4 PostgreSQLSQLite

11.1 DB2 LUW9iR1 Oracle

2012[0] SQL Server[0]Only as window function (requires OVER clause)

SQL:2011

OVERSQL:2011 groups option

OVER (groups option) Since SQL:2011ORDERBYx<frameunit>between1precedingand1following

OVER (groups option) Since SQL:2011ORDERBYx<frameunit>between1precedingand1following

rows,range

OVER (groups option) Since SQL:2011ORDERBYx<frameunit>between1precedingand1following

rows,range

x13

3.53.54

CURRENT ROW

OVER (groups option) Since SQL:2011ORDERBYx<frameunit>between1precedingand1following

rows,range

rowscount(*)

x13

3.53.54

CURRENT ROW

OVER (groups option) Since SQL:2011ORDERBYx<frameunit>between1precedingand1following

rows,range

rangexbetweencurrent_row-1

andcurrent_row+1

rowscount(*)

x13

3.53.54

CURRENT ROW

OVER (groups option) Since SQL:2011ORDERBYx<frameunit>between1precedingand1following

rows,rangeNew in

SQL:2011 groups

rangexbetweencurrent_row-1

andcurrent_row+1

rowscount(*)

x13

3.53.54

CURRENT ROW

groupscount(distinctx)

OVER (groups option) Since SQL:2011ORDERBYx<frameunit>between1precedingand1following

rows,rangeNew in

SQL:2011 groups

rangexbetweencurrent_row-1

andcurrent_row+1

rowscount(*)

x13

3.53.54

CURRENT ROW

Since SQL:2011OVER (groups option)1999

2001

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5.1 MariaDBMySQL

11 PostgreSQL3.28.0 SQLite

DB2 LUWOracleSQL Server

System Versioning (Time Traveling)

INSERTUPDATEDELETE

are DESTRUCTIVE

System Versioning The Problem

System Versioning Since SQL:2011Table can be system versioned, application versioned or both.

CREATETABLEt(...,

System Versioning Since SQL:2011Table can be system versioned, application versioned or both.

CREATETABLEt(...,start_tsTIMESTAMP(9)GENERATEDALWAYSASROWSTART,

System Versioning Since SQL:2011Table can be system versioned, application versioned or both.

CREATETABLEt(...,start_tsTIMESTAMP(9)GENERATEDALWAYSASROWSTART,end_tsTIMESTAMP(9)GENERATEDALWAYSASROWEND,

System Versioning Since SQL:2011Table can be system versioned, application versioned or both.

CREATETABLEt(...,start_tsTIMESTAMP(9)GENERATEDALWAYSASROWSTART,end_tsTIMESTAMP(9)GENERATEDALWAYSASROWEND,

PERIODFORSYSTEM_TIME(start_ts,end_ts)

System Versioning Since SQL:2011Table can be system versioned, application versioned or both.

CREATETABLEt(...,start_tsTIMESTAMP(9)GENERATEDALWAYSASROWSTART,end_tsTIMESTAMP(9)GENERATEDALWAYSASROWEND,

PERIODFORSYSTEM_TIME(start_ts,end_ts))WITHSYSTEMVERSIONING

System Versioning Since SQL:2011Table can be system versioned, application versioned or both.

ID Data start_ts end_ts1 X 10:00:00

UPDATE...SETDATA='Y'...

ID Data start_ts end_ts1 X 10:00:00 11:00:001 Y 11:00:00

DELETE...WHEREID=1

INSERT...(ID,DATA)VALUES(1,'X')

System Versioning Since SQL:2011

ID Data start_ts end_ts1 X 10:00:00

UPDATE...SETDATA='Y'...

ID Data start_ts end_ts1 X 10:00:00 11:00:001 Y 11:00:00

DELETE...WHEREID=1

INSERT...(ID,DATA)VALUES(1,'X')

System Versioning Since SQL:2011

ID Data start_ts end_ts1 X 10:00:00

UPDATE...SETDATA='Y'...

ID Data start_ts end_ts1 X 10:00:00 11:00:001 Y 11:00:00

DELETE...WHEREID=1

INSERT...(ID,DATA)VALUES(1,'X')

System Versioning Since SQL:2011

ID Data start_ts end_ts1 X 10:00:00

UPDATE...SETDATA='Y'...

ID Data start_ts end_ts1 X 10:00:00 11:00:001 Y 11:00:00

DELETE...WHEREID=1

ID Data start_ts end_ts1 X 10:00:00 11:00:001 Y 11:00:00 12:00:00

INSERT...(ID,DATA)VALUES(1,'X')

System Versioning Since SQL:2011

Although multiple versions exist, only the “current” one is visible per default.

After 12:00:00, SELECT*FROMt doesn’t return anything anymore.

ID Data start_ts end_ts1 X 10:00:00 11:00:001 Y 11:00:00 12:00:00

System Versioning Since SQL:2011

ID Data start_ts end_ts1 X 10:00:00 11:00:001 Y 11:00:00 12:00:00

With FOR…ASOF you can query anything you like: SELECT*FROMtFORSYSTEM_TIMEASOFTIMESTAMP'2019-05-0210:30:00'

ID Data start_ts end_ts

1 X 10:00:00 11:00:00

System Versioning Since SQL:2011

System Versioning Since SQL:20111999

2001

2003

2005

2007

2009

2011

2013

2015

2017

5.1 10.3 MariaDBMySQLPostgreSQLSQLite

10.1 DB2 LUW10gR1[0] 11gR1[1] Oracle

2016 SQL Server[0]Short term using Flashback.[1]Flashback Archive. Proprietery syntax.

FORPORTIONOF(UPDATE,DELETE)

CREATETABLEt(...,

Since SQL:2011Table can be system versioned, application versioned or both.

FOR PORTION OF

CREATETABLEt(...,start_tsTIMESTAMP(9),

Since SQL:2011Table can be system versioned, application versioned or both.

FOR PORTION OF

CREATETABLEt(...,start_tsTIMESTAMP(9),end_tsTIMESTAMP(9),

Since SQL:2011Table can be system versioned, application versioned or both.

FOR PORTION OF

CREATETABLEt(...,start_tsTIMESTAMP(9),end_tsTIMESTAMP(9),

PERIODFORapp(start_ts,end_ts))

Since SQL:2011Table can be system versioned, application versioned or both.

FOR PORTION OF

ID Data start_ts end_ts1 X 10:00:00 12:00:00

UPDATEtFORPORTIONOFappFROM'10:30:00'TO'11:30:00'SETDATA='Y'

ID Data start_ts end_ts1 X 10:00:00 10:30:001 Y 10:30:00 11:30:001 X 11:30:00 12:00:00

INSERTt(ID,DATA,start_ts,end_ts)VALUES(1,'X','10:00:00','12:00:00')

Since SQL:2011FOR PORTION OF

ID Data start_ts end_ts1 X 10:00:00 12:00:00

UPDATEtFORPORTIONOFappFROM'10:30:00'TO'11:30:00'SETDATA='Y'

ID Data start_ts end_ts1 X 10:00:00 10:30:001 Y 10:30:00 11:30:001 X 11:30:00 12:00:00

INSERTt(ID,DATA,start_ts,end_ts)VALUES(1,'X','10:00:00','12:00:00')

Since SQL:2011FOR PORTION OF

ID Data start_ts end_ts1 X 10:00:00 12:00:00

UPDATEtFORPORTIONOFappFROM'10:30:00'TO'11:30:00'SETDATA='Y'

ID Data start_ts end_ts1 X 10:00:00 10:30:001 Y 10:30:00 11:30:001 X 11:30:00 12:00:00

INSERTt(ID,DATA,start_ts,end_ts)VALUES(1,'X','10:00:00','12:00:00')

Since SQL:2011FOR PORTION OF

FORPORTIONOF Since SQL:20111999

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5.1 MariaDBMySQLPostgreSQLSQLite

10.5 DB2 LUWOracleSQL Server

10.4

FORPORTIONOF Since SQL:20111999

2001

2003

2005

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2013

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5.1 MariaDBMySQLPostgreSQLSQLite

10.5 DB2 LUWOracleSQL Server

10.4

Since SQL:2011Application Versioning

For a useful application versioning, WITHOUTOVERLAPS

constraints are required.

Apparently this was moved to MariaDB 10.5: https://jira.mariadb.org/browse/MDEV-16978

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Eichhörnchen

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