What's the difference between the text data type and the character varying (varchar) data types?
According to the documentation
If character varying is used without length specifier, the type accepts strings of any size. The latter is a PostgreSQL extension.
and
In addition, PostgreSQL provides the text type, which stores strings of any length. Although the type text is not in the SQL standard, several other SQL database management systems have it as well.
So what's the difference?
There is no difference, under the hood it's all varlena (variable length array).
Check this article from Depesz: http://www.depesz.com/index.php/2010/03/02/charx-vs-varcharx-vs-varchar-vs-text/
A couple of highlights:
To sum it all up:
char(n) – takes too much space when dealing with values shorter than n (pads them to n), and can lead to subtle errors because of adding trailing
spaces, plus it is problematic to change the limit
varchar(n) – it's problematic to change the limit in live environment (requires exclusive lock while altering table)
varchar – just like text
text – for me a winner – over (n) data types because it lacks their problems, and over varchar – because it has distinct name
The article does detailed testing to show that the performance of inserts and selects for all 4 data types are similar. It also takes a detailed look at alternate ways on constraining the length when needed. Function based constraints or domains provide the advantage of instant increase of the length constraint, and on the basis that decreasing a string length constraint is rare, depesz concludes that one of them is usually the best choice for a length limit.
As "Character Types" in the documentation points out, varchar(n), char(n), and text are all stored the same way. The only difference is extra cycles are needed to check the length, if one is given, and the extra space and time required if padding is needed for char(n).
However, when you only need to store a single character, there is a slight performance advantage to using the special type "char" (keep the double-quotes — they're part of the type name). You get faster access to the field, and there is no overhead to store the length.
I just made a table of 1,000,000 random "char" chosen from the lower-case alphabet. A query to get a frequency distribution (select count(*), field ... group by field) takes about 650 milliseconds, vs about 760 on the same data using a text field.
(this answer is a Wiki, you can edit - please correct and improve!)
UPDATING BENCHMARKS FOR 2016 (pg9.5+)
And using "pure SQL" benchmarks (without any external script)
use any string_generator with UTF8
main benchmarks:
2.1. INSERT
2.2. SELECT comparing and counting
CREATE FUNCTION string_generator(int DEFAULT 20,int DEFAULT 10) RETURNS text AS $f$
SELECT array_to_string( array_agg(
substring(md5(random()::text),1,$1)||chr( 9824 + (random()*10)::int )
), ' ' ) as s
FROM generate_series(1, $2) i(x);
$f$ LANGUAGE SQL IMMUTABLE;
Prepare specific test (examples)
DROP TABLE IF EXISTS test;
-- CREATE TABLE test ( f varchar(500));
-- CREATE TABLE test ( f text);
CREATE TABLE test ( f text CHECK(char_length(f)<=500) );
Perform a basic test:
INSERT INTO test
SELECT string_generator(20+(random()*(i%11))::int)
FROM generate_series(1, 99000) t(i);
And other tests,
CREATE INDEX q on test (f);
SELECT count(*) FROM (
SELECT substring(f,1,1) || f FROM test WHERE f<'a0' ORDER BY 1 LIMIT 80000
) t;
... And use EXPLAIN ANALYZE.
UPDATED AGAIN 2018 (pg10)
little edit to add 2018's results and reinforce recommendations.
Results in 2016 and 2018
My results, after average, in many machines and many tests: all the same (statistically less than standard deviation).
Recommendation
Use text datatype, avoid old varchar(x) because sometimes it is not a standard, e.g. in CREATE FUNCTION clauses varchar(x)≠varchar(y).
express limits (with same varchar performance!) by with CHECK clause in the CREATE TABLE e.g. CHECK(char_length(x)<=10). With a negligible loss of performance in INSERT/UPDATE you can also to control ranges and string structure e.g. CHECK(char_length(x)>5 AND char_length(x)<=20 AND x LIKE 'Hello%')
On PostgreSQL manual
There is no performance difference among these three types, apart from increased storage space when using the blank-padded type, and a few extra CPU cycles to check the length when storing into a length-constrained column. While character(n) has performance advantages in some other database systems, there is no such advantage in PostgreSQL; in fact character(n) is usually the slowest of the three because of its additional storage costs. In most situations text or character varying should be used instead.
I usually use text
References: http://www.postgresql.org/docs/current/static/datatype-character.html
In my opinion, varchar(n) has it's own advantages. Yes, they all use the same underlying type and all that. But, it should be pointed out that indexes in PostgreSQL has its size limit of 2712 bytes per row.
TL;DR:
If you use text type without a constraint and have indexes on these columns, it is very possible that you hit this limit for some of your columns and get error when you try to insert data but with using varchar(n), you can prevent it.
Some more details: The problem here is that PostgreSQL doesn't give any exceptions when creating indexes for text type or varchar(n) where n is greater than 2712. However, it will give error when a record with compressed size of greater than 2712 is tried to be inserted. It means that you can insert 100.000 character of string which is composed by repetitive characters easily because it will be compressed far below 2712 but you may not be able to insert some string with 4000 characters because the compressed size is greater than 2712 bytes. Using varchar(n) where n is not too much greater than 2712, you're safe from these errors.
text and varchar have different implicit type conversions. The biggest impact that I've noticed is handling of trailing spaces. For example ...
select ' '::char = ' '::varchar, ' '::char = ' '::text, ' '::varchar = ' '::text
returns true, false, true and not true, true, true as you might expect.
Somewhat OT: If you're using Rails, the standard formatting of webpages may be different. For data entry forms text boxes are scrollable, but character varying (Rails string) boxes are one-line. Show views are as long as needed.
A good explanation from http://www.sqlines.com/postgresql/datatypes/text:
The only difference between TEXT and VARCHAR(n) is that you can limit
the maximum length of a VARCHAR column, for example, VARCHAR(255) does
not allow inserting a string more than 255 characters long.
Both TEXT and VARCHAR have the upper limit at 1 Gb, and there is no
performance difference among them (according to the PostgreSQL
documentation).
The difference is between tradition and modern.
Traditionally you were required to specify the width of each table column. If you specify too much width, expensive storage space is wasted, but if you specify too little width, some data will not fit. Then you would resize the column, and had to change a lot of connected software, fix introduced bugs, which is all very cumbersome.
Modern systems allow for unlimited string storage with dynamic storage allocation, so the incidental large string would be stored just fine without much waste of storage of small data items.
While a lot of programming languages have adopted a data type of 'string' with unlimited size, like C#, javascript, java, etc, a database like Oracle did not.
Now that PostgreSQL supports 'text', a lot of programmers are still used to VARCHAR(N), and reason like: yes, text is the same as VARCHAR, except that with VARCHAR you MAY add a limit N, so VARCHAR is more flexible.
You might as well reason, why should we bother using VARCHAR without N, now that we can simplify our life with TEXT?
In my recent years with Oracle, I have used CHAR(N) or VARCHAR(N) on very few occasions. Because Oracle does (did?) not have an unlimited string type, I used for most string columns VARCHAR(2000), where 2000 was at some time the maximum for VARCHAR, and in all practical purposes not much different from 'infinite'.
Now that I am working with PostgreSQL, I see TEXT as real progress. No more emphasis on the VAR feature of the CHAR type. No more emphasis on let's use VARCHAR without N. Besides, typing TEXT saves 3 keystrokes compared to VARCHAR.
Younger colleagues would now grow up without even knowing that in the old days there were no unlimited strings. Just like that in most projects they don't have to know about assembly programming.
I wasted way too much time because of using varchar instead of text for PostgreSQL arrays.
PostgreSQL Array operators do not work with string columns. Refer these links for more details: (https://github.com/rails/rails/issues/13127) and (http://adamsanderson.github.io/railsconf_2013/?full#10).
If you only use TEXT type you can run into issues when using AWS Database Migration Service:
Large objects (LOBs) are used but target LOB columns are not nullable
Due to their unknown and sometimes large size, large objects (LOBs) require more processing
and resources than standard objects. To help with tuning migrations of systems that contain
LOBs, AWS DMS offers the following options
If you are only sticking to PostgreSQL for everything probably you're fine. But if you are going to interact with your db via ODBC or external tools like DMS you should consider using not using TEXT for everything.
character varying(n), varchar(n) - (Both the same). value will be truncated to n characters without raising an error.
character(n), char(n) - (Both the same). fixed-length and will pad with blanks till the end of the length.
text - Unlimited length.
Example:
Table test:
a character(7)
b varchar(7)
insert "ok " to a
insert "ok " to b
We get the results:
a | (a)char_length | b | (b)char_length
----------+----------------+-------+----------------
"ok "| 7 | "ok" | 2
Postgres (V11.3, 64bit, Windows) truncates trailing zeros for timestamps. So if I insert the timestamp '2019-06-12 12:37:07.880' into the table and I read it back as text postgres returns '2019-06-12 12:37:07.88'.
Table date_test:
CREATE TABLE public.date_test (
id SERIAL,
"timestamp" TIMESTAMP WITHOUT TIME ZONE NOT NULL,
CONSTRAINT pkey_date_test PRIMARY KEY(id)
)
SQL command when inserting data:
INSERT INTO date_test (timestamp) VALUES( '2019-06-12 12:37:07.880' )
SQL command to retrieve data:
SELECT dt.timestamp ::TEXT FROM date_test dt
returns '2019-06-12 12:37:07.88'
Do you consider this a bug or a feature?
My real issue is: I´m running queries from a C++ program and I have to convert the data returned from the database to appropriate data types. Since the protocol is text-based everything I read from the database is plain text. When parsing timestamps I first tokenize the string and then convert each token to integer. And because the millisecond part is truncated, the last token is "88" instead of "880", and converting "88" yields another value that converting "880" to integer.
That's the default display format when using a cast to text.
If you want to see all three digits, use to_char()
SELECT to_char(dt.timestamp,'yyyy-mm-d hh24:mi:ss.ms')
FROM date_test dt;
will return 2019-06-12 12:37:07.880
It’s a matter of presentation only.
First note that 07.88 seconds and 07.880 seconds is the same amount of time (also 7.88 and 07.880000000 for that matter).
PostgreSQL internally represents a timestamp in a way that we shouldn’t be concerned about as long as it’s an unambiguous representation. When you retrieve the timestamp, it is formatted into some string. This is where PostgreSQL apparently chooses not to print redundant trailing zeros. So it’s probably not even correct to say that it truncates anything. It just refrains from generating that 0.
I think that the nice solution would be to modify your parser in C++ to accept any number of decimals and parse them correctly with and without trailing zeroes. Another solution that should work is given in the answer by a_horse_with_no_name.
I have a table on PostgreSQL with a field named data that is jsonb with a lot of objects, I want to make an index to speed up the queries. I'm using few rows to test the data (just 15 rows) but I don't want to have problems with the queries in the future. I'm getting data from the Twitter API, so with a week I get around 10gb of data. If I make the normal index
CREATE INDEX ON tweet((data->>'created_at'));
I get a text index, if I make:
Create index on tweet((CAST(data->>'created_at' AS timestamp)));
I get
ERROR: functions in index expression must be marked IMMUTABLE
I've tried to make it "inmutable" setting the timezone with
date_trunc('seconds', CAST(data->>'created_at' AS timestamp) at time zone 'GMT')
but I'm still getting the "immutable" error. So, How can I accomplish a timestamp index from a JSON? I know that I could make a simple column with the date because probably it will remain constant in the time, but I want to learn how to do that.
This expression won't be allowed in the index either:
(CAST(data->>'created_at' AS timestamp) at time zone 'UTC')
It's not immutable, because the first cast depends on your DateStyle setting (among other things). Doesn't help to translate the result to UTC after the function call, uncertainty has already crept in ...
The solution is a function that makes the cast immutable by fixing the time zone (like #a_horse already hinted).
I suggest to use to_timestamp() (which is also only STABLE, not IMMUTABLE) instead of the cast to rule out some source of trouble - DateStyle being one.
CREATE OR REPLACE FUNCTION f_cast_isots(text)
RETURNS timestamptz AS
$$SELECT to_timestamp($1, 'YYYY-MM-DD HH24:MI')$$ -- adapt to your needs
LANGUAGE sql IMMUTABLE;
Note that this returns timestamptz. Then:
CREATE INDEX foo ON t (f_cast_isots(data->>'created_at'));
Detailed explanation for this technique in this related answer:
Does PostgreSQL support "accent insensitive" collations?
Related:
Query on a time range ignoring the date of timestamps
I am creating a table that will be populated with a COPY. Here's the format of that data:
6/30/2014 2:33:00 PM
MM-DD-YYYY HH:MM:SS ??
What would I use as the formatting for the CREATE TABLE statement?
CREATE TABLE practice (
Data_Time ????
)
One alternative might be to read as varchar() then format later. Seems convoluted tho.
Always store timestamps as timestamp (or timestamptz).
Never use string types (text, varchar, ...) for that.
CREATE TABLE practice (
practice_id serial PRIMARY KEY
, data_time timestamp NOT NULL
);
If your timestamp literals are clean and follow the standard MDY format, you can set the DateStyle temporarily for the transaction to read proper timestamp types directly:
BEGIN;
SET LOCAL datestyle = 'SQL, MDY'; -- works for your example
COPY practice (data_time) FROM '/path/to/file.csv';
COMMIT;
Else, your idea is not that bad: COPY to a temporary table with a text column, sanitize the data and INSERT timestamps from there possibly using to_timestamp(). Example:
Formatting Date(YY:MM:DD:Time) in Excel
You should pretty much never use vharchar() in postgres. Always use text. But it sounds to me like you want 2 columns
create table practice (date_time timestamp, format text)
I have two tables,
details
id integer primary key
onsetdate Date
questionnaires
id integer primary key
patient_id integer foreign key
questdate Character Varying
Is it possible to make a SELECT statement that performs a JOIN on these two tables, ordering by the earliest date taken from a comparision of onsetdate and questdate (is it possible for example to cast the questdate into a Date field to do this?)
Typical format for questdate is "2009-04-22"
The actual tables have an encyrpted BYTEA field for the onsetdate - but I'll leave that part until later (the application is written in RoR using 'ezcrypto' to encrypt the BYTEA field).
something like
SELECT...
FROM details d
JOIN quesionnaires q ON d.id=q.id
ORDER BY LEAST (decrypt_me(onsetdate), questdate::DATE)
maybe? i'm not sure about the meaning of 'id', if you want to join by it or something else
By the way, you can leave out the explicit cast, it's in ISO format after all.
I guess you know what to use in place of decrypt_me()
There is a date parsing function in postgres: http://www.postgresql.org/docs/9.0/interactive/functions-formatting.html
Look for the to_timestamp function.
PostgreSQL supports the standard SQL CAST() function. (And a couple others, too.) So you can use
CAST (questdate AS DATE)
as long as all the values in the column 'questdate' evaluate to a valid date. If this database has been in production for a while, though, that's pretty unlikely. Not impossible, but pretty unlikely.