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METHODS TO INSERT DATA INTO SQL SERVER

April 10, 2019 by Ed Pollack


SUMMARY

There are a variety of ways of managing data to insert into SQL Server. How we
generate and insert data into tables can have a profound impact on performance
and maintainability! This topic is often overlooked as a beginner’s
consideration, but mistakes in how we grow objects can create massive headaches
for future developers and administrators.

In this article we will explore the different ways we can create and insert data
into both permanent and temporary objects. Performance, syntax, documentation,
and maintainability will be evaluated for each method. By delving deeper into
this topic, we can improve database design, script quality, and build objects
that are easier to upkeep and less likely to break due to maintenance or
software releases.


DEMO DATA

All demos in this article will use new objects we create here. This will allow
us full reign to customize, test, and break it independently of anything else we
are working on.

The following is the TSQL to create a table called dbo.accounts:



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CREATE TABLE dbo.account
( account_id INT NOT NULL IDENTITY(1,1) CONSTRAINT PK_account PRIMARY KEY
CLUSTERED,
  account_name VARCHAR(100) NOT NULL,
  account_start_date DATE NOT NULL,
  account_address VARCHAR(1000) NOT NULL,
  account_type VARCHAR(10) NOT NULL,
  account_create_timestamp DATETIME NOT NULL,
    account_notes VARCHAR(500) NULL,
  is_active BIT NOT NULL);



This is a fairly simple table with an identity ID and some string/date columns
for account data. As we work through this article, we will add and remove
columns, as well as customize this further.


INSERT DATA INTO SQL SERVER USING AN EXPLICIT COLUMN LIST

Let’s begin by diving straight into some of the simplest of syntaxes in T-SQL:
The INSERT statement. The most common way to insert rows into a table is by
doing so with an INSERT statement where we explicitly cite the entire column
list prior to providing the values:



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INSERT INTO dbo.account
  (account_name, account_start_date, account_address, account_type,
account_create_timestamp, account_notes, is_active)
VALUES
  ('Ed''s Account',
   '5/1/2019',
   'Ed''s Address',
   'TEST',
   GETUTCDATE(),
   'This is a test account to model this data.',
   0);



In this example, we provide a complete column list and use the VALUES syntax to
list out scalar values to insert into the table. If desired, we can insert
multiple rows via this syntax, separating each row by a comma.

We also have the option of omitting columns from the column and SELECT lists.
This can be used for columns that allow NULL (and we want to be left NULL), or
for columns that have default constraints defined on them (and we want the
column to accept the default value). The following example shows an account
insertion where we omit the account_notes column:



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INSERT INTO dbo.account
  (account_name, account_start_date, account_address, account_type,
account_create_timestamp, is_active)
VALUES
  ('Initech',
   '2/19/1999',
   '4120 Freidrich Ln.',
   'LIVE',
   GETUTCDATE(),
   1);



After the two above insertions, we can view the resulting data and note that the
results are what we expect:



SQL Server allowed us to omit the account_notes column and in doing so assigned
NULL in its place. Let’s add a default constraint to this column:



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ALTER TABLE dbo.account ADD CONSTRAINT DF_account_account_notes DEFAULT ('NONE
PROVIDED') FOR account_notes;



With a default constraint on the column, we may test another INSERT where we
intentionally leave out the account_notes column:



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INSERT INTO dbo.account
  (account_name, account_start_date, account_address, account_type,
account_create_timestamp, is_active)
SELECT
  'Dinosaur Corp',
  '1/1/2003',
  'The Triassic Time Period',
  'DEMO',
  GETUTCDATE(),
  1;



The results show us how the new row looks in our table:



We can see that the default value from the constraint was applied to
account_notes, as expected. Creating a default constraint can be useful for
ensuring that a column can be made NOT NULL and always be assigned a value. It
is also useful when we wish to have a column that typically is not assigned a
value, but requires one for an application or reporting purpose. A default
constraint should never be used to generate placeholder, fake, or obfuscated
data. For example, -1 is a poor choice for an integer column and 1/1/1900 is a
lousy choice for a date column as each provides confusing meaning that is not
intuitive to a developer or someone consuming this data.

The primary benefit of inserting data with an explicit column list are that you
document exactly what columns are being populated, and what data is being put
into each column. If a column is left off the list, then it will be made NULL.
If a NOT NULL column with no default constraint is left off of the list, an
error will be thrown, similar to this:



Similarly, if you accidentally leave off a column from the column list, you’ll
get this error:



As a result, the explicitly provided column list makes it hard to accidentally
leave columns out.

This syntax has a downside, though, and that is maintainability in scenarios
where table schema changes often and there is a desire to always SELECT *. If
you are dumping data to an output table and do not care about column order,
typing, or quantity, then having to always adjust the column list to match the
SELECT details may be a hassle and not worth the effort.


INSERT DATA INTO SQL SERVER WITHOUT AN EXPLICIT COLUMN LIST

This leads us into the alternative way to insert data into an existing table,
which is to do so without a column list. An insert of this form will look like
this:



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INSERT INTO dbo.account
SELECT
  'The Pokemon Company',
  '4/23/1998',
  'Roppongi Hills Mori Tower 8F, Tokyo, Japan',
  'LIVE',
  GETUTCDATE(),
  'Very valuable.  They make all the Pokemon!',
   1;



This statement executes successfully, despite no column list being provided.
When SQL Server binds this query to its underlying objects, it will pull the
column list in order and apply it to the data being inserted. If everything
matches up, then we’re good to go, otherwise we will receive an error similar to
the two we saw earlier that indicate column lists that do not match up.

The upside (if we wish to call it an upside) of this approach is that it is fast
and requires less upkeep as there’s no need to write and maintain a list of
columns with the insert. The downside is that if you mismatch columns, you may
get a different sort of error message. Consider the following query:



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INSERT INTO dbo.account
SELECT
  'The Pokemon Company',
  '4/23/1998',
  'Roppongi Hills Mori Tower 8F, Tokyo, Japan',
  GETUTCDATE(),
  'Very valuable.  They make all the Pokemon!',
   0;



When executed, we get a new error message:



In this scenario, we left out a column, but since this table includes NULLable
columns, SQL Server tried to match up the table’s columns anyway using the data
we provided, but was unable to make a meaningful match.

Because of the potential for confusing errors and the inability to easily match
up columns to data, inserting into a table without providing a column list is
not seen as a best practice and should be avoided whenever possible. I would
recommend including a column list in all INSERT statements unless you happen to
have a very unique use-case in which the convenience of the simpler syntax
outweighs the risk of future code breaking if the table’s schema changes.

In addition, the column list provides clear documentation to the user as to what
is being inserted and which columns the data will be going into. We can improve
upon this further if we wish by adding aliases to all inserted columns:



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INSERT INTO dbo.account
  (account_name, account_start_date, account_address, account_type,
account_create_timestamp, account_notes, is_active)
SELECT
  'Microsoft' AS account_name,
  '4/4/1975' AS account_start_date,
  'One Microsoft Way in Redmond, Washington' AS account_address,
  'LIVE' AS account_type,
  GETUTCDATE() AS account_start_date,
  'They make SQL Server.  Thanks!' AS account_notes,
   1 AS is_active;



Adding column aliases may seem like overkill, but when working with longer
INSERT statements, dynamic SQL, or complex queries, the added documentation can
greatly aid in writing, modifying, and troubleshooting those queries. You can
also test your insert statement by highlighting the SELECT list only and
executing it, which returns values along with the handy column headers:



Alternatively, you can provide that documentation in comments:



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INSERT INTO dbo.account
  (account_name, account_start_date, account_address, account_type,
account_start_date, account_notes, is_active)
SELECT
  'Microsoft', -- account_name
  '4/4/1975', -- account_start_date
  'One Microsoft Way in Redmond, Washington', -- account_address
  'LIVE', -- account_type
  GETUTCDATE(), -- account_start_date
  'They make SQL Server.  Thanks!', -- account_notes
   1; -- is_active



This can be a nice way to document without adjusting the query. The only
downside is that you lose the handy column names that were demonstrated above
with the test SELECT. Both are worth the extra 30 seconds to include in your
code as they will save far more time in the future when the time comes to modify
or troubleshoot that code.


INSERT DATA INTO SQL SERVER WITH SELECT INTO

It is possible to create a new table object and SELECT data into it as a part of
a single statement. This can be a convenient way to avoid the hassle of defining
a table up-front and enumerating column names. Typically this is used to
populate temporary tables, but it could be used for permanent tables if a
scenario called for it. SELECT INTO may not be used to automatically create
table variables.



The query below shows how we can accomplish this task quickly and efficiently:



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SELECT
  'Ed Pollack' AS developer_name,
  'SQL Server 2019 CTP1' AS database_engine_of_choice,
  'Pizza' AS food_choice,
  10 AS spice_level
INTO #developer_info;



When executed, a temporary table will be created on-the-fly with the column
names provided. When we query the table, we get the following results:



The data types for the columns are automatically chosen by SQL Server. We can
verify them by querying TempDB as follows:



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SELECT
  tables.name AS TableName,
  columns.name AS ColumnName,
  columns.max_length AS ColumnLength,
  types.name AS TypeName
FROM TempDB.sys.tables
INNER JOIN TempDB.sys.columns
ON tables.object_id = columns.object_id
INNER JOIN TempDB.sys.types
ON types.user_type_id = columns.user_type_id
WHERE tables.name LIKE '#developer_info%';



The results show columns that were sized to meet the minimum needs of the data
that I inserted:



Had I inserted multiple rows, then the column sizes would match the smallest
sizes needed to fit all of that data. This is amazingly convenient assuming that
we do not need to add additional data to the temporary table later. If we do, we
would need to ensure that the new data does not exceed the column sizes that
have already been defined.

The SELECT INTO syntax provides a huge convenience when we want to insert data
into a table that may vary greatly from execution-to-execution, or that may
undergo schema changes often enough so as to make the maintenance of column
lists challenging.

You can control data types if you wish. Let’s repeat our example above using the
following TSQL:



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SELECT
  CAST('Ed Pollack' AS VARCHAR(50)) AS developer_name,
  CAST('SQL Server 2019 CTP1' AS VARCHAR(30)) AS database_engine_of_choice,
  CAST('Pizza' AS VARCHAR(25)) AS food_choice,
  CAST(10 AS DECIMAL(5,2)) AS spice_level
INTO #developer_info;



When we consult with system views, we can confirm that the data types have been
defined as we wanted them and not as the minimal sizes required to support the
data that I created:



The primary downside of using the SELECT INTO syntax is that the resulting table
will have no indexes or constraints defined on it. If any additional structure
is required for the table, it will need to be added after-the-fact. For
scenarios where this is not needed, then SELECT INTO provides a very fast and
convenient syntax that can shorten code and improve maintainability by reducing
the number of places that require change when the data’s underlying schema or
definition undergo change.

SELECT INTO can also be used for a generic SELECT statement with no additional
definitions, such as this:



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SELECT
  *
INTO dbo.account_backup
FROM dbo.account;



In a very short TSQL statement, we created a new permanent table and inserted
all of the contents of dbo.account into it. Note that when this syntax is used,
the data types in the resulting table will match the source table as they are
currently defined.


INSERT DATA SQL SERVER VIA STORED PROCEDURE OR DYNAMIC SQL

Stored procedures are often used to return data to applications, reports, or
additional TSQL scripts for processing. The results of any stored procedure can
be inserted directly into a predefined table like this:



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CREATE TABLE #temp
( SPID VARCHAR(100),
  STATUS VARCHAR(100),
  LOGIN VARCHAR(100),
  hostname VARCHAR(100),
  blkby VARCHAR(100),
  dbname VARCHAR(100),
  command VARCHAR(100),
  cputime VARCHAR(100),
  diskit VARCHAR(100),
  latbatch VARCHAR(100),
  programname VARCHAR(100),
  spid2 VARCHAR(100),
  requestid VARCHAR(100))
INSERT INTO #temp
EXEC sp_who2;
 
SELECT * FROM #temp
WHERE dbname = 'AdventureWorks2016CTP3';
DROP TABLE #temp;



This monitoring script will execute sp_who2 to return a list of current
processes in a given database. By default, this stored procedure returns all
sessions, though parameters can be supplied to filter by login or session ID. To
filter by database, though, would otherwise require returning all data and then
manually removing the irrelevant rows. By creating a temporary table up front
and inserting the results directly into it, we are then freed up to filter the
result set by whatever criteria we wish. Any table may be used for this purpose,
including permanent tables, as well as table variables.

The same syntax can be used to insert the results of dynamic SQL into a table,
like this:



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DECLARE @sql_command NVARCHAR(MAX);
DECLARE @account_type SYSNAME = 'LIVE';
SELECT @sql_command = '
  SELECT
    account_id
  FROM dbo.account
  WHERE account_type = ''' + @account_type + ''';';
CREATE TABLE #id_list
  (account_id INT NOT NULL PRIMARY KEY CLUSTERED);
 
INSERT INTO #id_list
  (account_id)
EXEC sp_executesql @sql_command;
 
SELECT * FROM #id_list;
DROP TABLE #id_list;



The end result of this code is that we use sp_executesql to execute dynamic SQL,
placing the results directly into a temporary table.

In both of these scenarios, we were able to execute procedural TSQL and insert
the results directly into an existing table. SELECT INTO is not supported with
this syntax, but everything else we have discussed so far does work with this
convention.


INSERT DATA SQL SERVER WITH OUTPUT INSERTED

A bonus way we can generate data is via an existing statement. When we execute
any write operation, we may output data from before or after the change to
another table. Here is an example of how this looks:



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CREATE TABLE #account_ids
  (account_id INT NOT NULL PRIMARY KEY CLUSTERED);
 
UPDATE account
  SET is_active = 1
OUTPUT INSERTED.account_id
INTO #account_ids
FROM dbo.account
WHERE account_type = 'LIVE';
 
SELECT * FROM #account_ids;
 
DROP TABLE #account_ids;



The goal above is to update all accounts of type “LIVE” to be active. We also
want to return the account_id for each account that was updated. Using OUTPUT
INSERTED allows us to accomplish both tasks in a single set-based solution. The
results show us which IDs were affected by the update statement:



INSERTED will contain all columns in the table as they appear after changes have
been applied. Similarly, DELETED will contain the previous versions. We can mix
and match these for maximum effect:



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CREATE TABLE #account_ids
  (account_id INT NOT NULL PRIMARY KEY CLUSTERED, is_active_previous BIT NOT
NULL, is_active_current BIT NOT NULL);
 
UPDATE account
  SET is_active = 0
OUTPUT INSERTED.account_id,
     DELETED.is_active,
     INSERTED.is_active
INTO #account_ids
FROM dbo.account
WHERE account_type = 'LIVE';
 
SELECT * FROM #account_ids;
 
DROP TABLE #account_ids;



The results show that we not only captured the account IDs, but also the
previous and new values for the is_active flag. This is a huge convenience as we
can use OUTPUT INSERTED in INSERT, DELETE, UPDATE, and MERGE statements to
quickly pull before & after data for use in additional processing.

This is a far superior solution to iteration and/or using SCOPE_IDENTITY() and
is the only easy way to capture data in this fashion with so little code. OUTPUT
INSERTED is a great method for getting before & after data from DML statements.
It is also useful for collecting a list of rows that were altered in a given
TSQL statement, so we can take additional actions or report on them as needed.


WHICH METHOD IS BEST?

With a variety of methods to insert data into SQL Server available, the first
question we will ask is which syntax should we use? The answer is going to
depend on your use-case and specifically what is most important to a given
application. To summarize our work so far:

Use an INSERT with an explicit column list for applications where column lists,
inputs, and outputs do not change often. These are scenarios where change
typically consist of column additions or alterations resulting from software
releases. The column lists also add a layer of protection against logical errors
if a column is added, removed, or altered without the INSERT statement also
being updated. An error being thrown is a far better outcome than data quietly
being handled incorrectly. This syntax is generally considered a best practice
as it provides both documentation and protection against inadvertent mistakes
should the schema change in the future.

An INSERT with no column list carves out a niche in scenarios where the columns
are unknown or frequently changing. This might be useful in ETL, reporting, or
scenarios involving transient data when the data is unstructured. Despite that
possible application, I would lean towards using SELECT INTO for these
applications as they provide a bit more safety against inadvertent mistakes with
your data. An alternative to cover the need to insert into a pre-existing table
would be to use SELECT INTO to create a temporary data structure and then insert
from that temporary data into the permanent table using a formal column list.

SELECT INTO provides us the ability to quickly create a new table and dump data
into it with very little setup or coding. For small data sets or those that are
going to be scanned in their entirety, this is a great way to move data with
minimal TSQL and maintenance. The primary downside is the inability to include
indexes or constraints on the table until after it is created. This syntax must
create a new table, which lends itself towards using temporary tables as a
target to insert data to.

OUTPUT INSERTED allows us to return data from before, after, or before and after
a DML statement. This is a hugely useful syntax and one that has no intrinsic
downsides. It is a great alternative to iteration, functions, or triggers that
may attempt to accomplish the same tasks. The syntax is relatively simple and
can be applied to any data elements prior to or after a given change. You may
even include data that is not directly affected by a DML statement, but was
joined for use in the query!


CONCLUSION

There are many ways to insert data into SQL Server, but not all were created
equal. Picking the right syntax can have a significant impact on performance,
documentation, and maintainability. This article provides a comparison of a
variety of syntaxes, as well as the pros, cons, and demos of each one.

Always consider your application when writing code and adjust your style based
on how often schema and code are expected to change. Schema and applications
that are static and rarely changed can afford to have hard-coded INSERT
statements with columns, aliases, and/or reference documentation to make them
easy to read and maintain.

For schema or business needs that changes often, SELECT INTO or the omission of
the column list from an INSERT may allow for more fluidity in places where code
would greatly benefit from it.

Having a variety of options at our disposal allows us to make better decisions
when smart choices are needed and will help us write better code that will make
future developers appreciate us that much more as it is updated and maintained!


REFERENCES AND FURTHER READING

 * MSDN reference for OUTPUT INSERTED and general use of the OUTPUT clause
 * Demos of how to use system catalog views from Microsoft’s documentation
 * Microsoft’s Extensive documentation on the INSERT statement


SEE MORE

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 * Author
 * Recent Posts

Ed Pollack

Ed has 20 years of experience in database and systems administration, developing
a passion for performance optimization, database design, and making things go
faster.He has spoken at many SQL Saturdays, 24 Hours of PASS, and PASS
Summit.This lead him to organize SQL Saturday Albany, which has become an annual
event for New York’s Capital Region.

In his free time, Ed enjoys video games, sci-fi & fantasy, traveling, and being
as big of a geek as his friends will tolerate.

View all posts by Ed Pollack
Latest posts by Ed Pollack (see all)
 * SQL Server Database Metrics - October 2, 2019
 * Using SQL Server Database Metrics to Predict Application Problems - September
   27, 2019
 * SQL Injection: Detection and prevention - August 30, 2019




RELATED POSTS:

 1. INSERT INTO SELECT statement overview and examples
 2. Overview of the SQL Insert statement
 3. Learn SQL: INSERT INTO TABLE
 4. SQL Server Data Type Conversion Methods and performance comparison
 5. Two methods for restoring a data warehouse/data mart environment

Development, Performance, T-SQL


ABOUT ED POLLACK

Ed has 20 years of experience in database and systems administration, developing
a passion for performance optimization, database design, and making things go
faster. He has spoken at many SQL Saturdays, 24 Hours of PASS, and PASS Summit.
This lead him to organize SQL Saturday Albany, which has become an annual event
for New York’s Capital Region. In his free time, Ed enjoys video games, sci-fi &
fantasy, traveling, and being as big of a geek as his friends will tolerate.
View all posts by Ed Pollack

View all posts by Ed Pollack →
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