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Hi Farhin, can't tell from what you've posted. I've worked with high volume options data, where the number is specific to 6 decimal places even for USD, so we we use (18,6). It contains SQL Overview, RDBMS Concepts, Entity Relationship Model, SQL Constraints, Integrity, Normalization, Tables, Index, SQL Joins, Views, SQL Stored Procedures, SQL Functions, SQL Triggers, SQL Cursors and SQL Standards & Performance Tips. for DECIMAL(18,2) and NUMERIC(18,2)? In terms of mathematics they are same but not in terms of memory and precision. The precision must be a value from 1 through the maximum precision of 38. PRINT @Value; is giving below, output: END; While there are examples where taking a value, and dividing by a proportion is going to finally total closer to the original amount, that's not an argument for storing values as approximate values. Use SQL server's decimal type. FLOAT stores numbers in approximate precision. Although double-precision floating point numbers are approximate, they often give me a closer result to original numbers due to the number of decimal places they store. DevOps: Load Tests Need to be Part of Your Regular Deployments, https://docs.microsoft.com/en-us/sql/t-sql/data-types/precision-scale-and-length-transact-sql?WT.mc_id=DP-MVP-7914, SDU Tools: Strip diacritics from strings in SQL Server T-SQL, BI: DataWeek starting soon – don't miss it, SDU Podcast: Show 80 with guest Pedro Lopes is now available, ADF: Time zone support in Data Factory – a Small Change but so Important, SQL: Newbie Mistake #1: Using float instead of decimal, General: PowerPoint – sorry we couldn't find slide1.PNG – Unexpected space. One of those is the extensive use of the float data type. Float data type stores numeric data with floating decimal precision. float is used to store approximate values, not exact values. The exact numeric data types are SMALLINT, INTEGER, BIGINT, NUMERIC(p,s), and DECIMAL(p,s). And as you say, there's no silver bullet on this one. SQL Server 2008 :: Difference Between Money And (Float Or Decimal) Datatype Jan 16, 2013. Or am I mistaken? So why does it show 10 in the Messages tab? I tested it in SQL Server Management Studio on a SQL Server database (version 10.50.1600.1). I generally don’t use those. So, now let us how we can use the powerful decimal & float datatype of MySQL to store fractional numericals on the database… MySQL FLOAT vs DEC (concept analysis): One may get confused that decimal and float both are the same. In this article we will focus on two types of data; the decimal and the double data types. But this trade-off comes at the cost of precision. Float stores an approximate value and decimal stores an exact value. When I'm doing this over more than one record then differences start to creep in versus the whatever I'm comparing against (usually source data). decimal[(p[, s])] p (precision) Specifies the maximum total number of decimal digits that can be stored, both to the left and to the right of the decimal point. Real heavyweights: Float vs Decimal, the Thrilla in Precision This is a followup to a previous post where I likened SQL Server float datatype to Muhammad Ali. 1221 South MoPac Expressway It could be as you say, that it is rounding/formatting the results for whatever reason, but then shouldn't the same happen when adding? With rounding, it can be the luck of the draw as to what values you're working with. The basic difference between Decimal/Numeric and Float : Float is Approximate-number data type, which means that not all values in the data type range can be represented exactly. possible values look like this 1.0, 1.25 or 1.5 PercentDiscount (float) - holds a percentage For example, see the difference if you used decimal(38,20) instead of just decimal. Where as DECIMAL stores in exact and exactly the same precision defined before. There are some situations where float makes sense, but 99% of the time what they should have used was decimal. For example Google OR-Tools requires double data type, anything decimal has to be converted during Google lib function calls which makes run-time longer for huge number of rows. I don't find this example dishonest. I created 3 test tables with 1 column, one was decimal(6, 2), one float, and one double. 1 4020447649 (for 63407.0000) Result: 12510.848494783. In SQL, numbers are defined as either exact or approximate. money and smallmoney are old Sybase data types that have fixed scale, and have a funky relationship with currency symbols when converting strings. Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube. Organizations deal with decimals on a day-to-day basis, and these decimal values can be seen everywhere in different sectors, be it in banks, the medical industry, biometrics, gas stations, financial reports, sports, and whatnot. Numeric data types are exact data types that store values of a specified precision and scale, expressed with a number of digits before and after a decimal point.This contrasts with the Vertica integer and floating data types: DOUBLE PRECISION (FLOAT) supports ~15 digits, variable exponent, and represents numeric values approximately. Not sure I quite follow the issue, but the fact that something has worked for many years doesn't mean that it's correct. For example, if I need to pay someone \$100 quarterly, and send them 1/3 of that each month, I can't actually send them \$33.33333333333333333333333333 each month, even though it would total to close to the right value at the end. postion = 63407.00000 real is similar but is an IEEE standard floating point value, equivalent to float (24). Like the real data type, float data is approximate: float can hold 8 bytes, or 15 places after the decimal point. Hi Edgar, typically when storing scientific values, rather than business values. It's just that whatever was showing you the value had rounded it as part of displaying it. SET @Value = @Value + @ExchangeRate; I need to send them \$33.33 (rounded to the nearest cent) for each of the first two months, and \$33.34 for the final month. and for other successful record it is giving sum(position) as it position. Float - … set @CONVERSION=1.0 Float and Real are approximate data types. Keep in mind that this is a relatively small amount of records (60,000) and the more data you have, the larger the variance will be. Should I be using Decimal or Double for everything instead? I inserted the same 100 values into each table. Float and Real data types do not store exact values for many numbers.The value can be extremely closed. You can’t blame people for using a data type called money for storing amounts of money. As I said, you need to store values appropriately and manage rounding. More generally, most examples I've seen of when floats become a problem are when adding, but it seems that some kind of black magic happens when multiplying? Ive read different articles regarding and this is the clearest of all! The two data types are categorized as part of the numeric data types. So in this case my float value will be much more precise compare to your decimal. Real is a Single Precision Floating Point number, while Float is a Double Precision Floating Point number.The Floating point numbers can store very large or very small numbers than decimal numbers. now, The maximum precision is 38. 1 5145766756 (for 72731.00000). Next, I will create new user defined functions to validate integer and decimal values as per my use case. The float and decimal tables are 1.7MB in size. Hi Arthur, yes, the rules for precision calculations are tricky. This is no longer a restriction as of SQL Server 2016 (13.x). Let’s now look at the query from before if we change to decimal: When executed, it stops exactly as expected: Decimal (and numeric) require a precision and a scale. Navigate: Previous Message • Next Message id position In contrast, integer and decimal data types are exact numeric values. There are some situations where float makes sense, but 99% of the time what they should have used was decimal. Standard SQL requires that DECIMAL(5,2) be able to store any value with five digits and two decimals, so values that can be stored in the salary column range from -999.99 to 999.99. It’s one of the problems with backwards compatibility in SQL Server. I appreciate there probably isn't a silver bullet solution for this but I would at least like to find a good intermediary solution. But there is a more important distinction exists: What values should this code print? Real heavyweights: Float vs Decimal, the Thrilla in Precision This is a followup to a previous post where I likened SQL Server float datatype to Muhammad Ali. The default precision is 18… One solution is obviously to reduce scale (i.e. Result: 12510.848494, Float: Thanks a lot. SELECT (@CONVERSION*10.25), DECLARE @CONVERSION1 decimal In standard SQL, the syntax DECIMAL(M) is equivalent to DECIMAL(M,0). END; DECLARE @Value float=0.9 Each monetary value is then still precise. My goal is always to be as accurate as possible when storing data and performing arithmetic functions, so 99% of the time I use Decimal data type. But this trade-off comes at the cost of precision. The default precision for this datatype is 126 binary or 38 decimal. BEGIN But if you just run the SELECT statement you get 7,99999999999999. Float stores an approximate value and decimal stores an exact value. The Decimal, Double, and Float variable types are different in the way that they store the values. In most financial organizations that I work in, exchange rates are calculated and stored to a particular number of decimal places, and there are rounding rules that need to be applied when performing calculations on them. Because the values cannot be stored precisely, people who use float end up with values that don’t match, columns of values that don’t quite add up, or totals that are a cent out, etc. SELECT (@CONVERSION/3)*3, and your first example with the counter, try running the following one, and see which one works…. real is similar but is an IEEE standard floating point value, equivalent to float(24). It will stored the values with exact precision and scale what you have defined. Numeric/Decimal are fixed precision data types. Precision is the main difference where float is a single precision (32 bit) floating point data type, double is a double precision (64 bit) floating point data type and decimal is a 128-bit floating point data type. Therefore if you have a float there is processing needed to convert that SQL float to a decimal value; beside that an float value often not give the decimal true value likewise a decimal. Decimal’s declaration and functioning is similar to Double. But there is one big difference between floating point values and decimal (numeric) values. 1/3 is 0.33333 recurring. Multiplication always seem to give me correct results, while addition produces float-rounding errors. QtyInvoiced (float) - holds the number of items invoice. The approximate numeric data types are FLOAT(p), REAL, and DOUBLE PRECISION. BEGIN The DECIMAL and NUMERIC keywords are interchangeable. If I say that an exchange rate is 0.1, I want it to be 0.1 not 0.9999 recurring. In summary, exact values like money should use decimal, and approximate values like scientific measurements should use float. These should be chosen appropriately to store the values that you need. Although it is still useful for many types of scientific calculations, particularly those that conform to the double-precision IEEE 754 standard for floating point arithmetic, it is, of necessity, a compromise. Numeric/Decimal are fixed precision data types. By continuing to browse or closing this banner, you indicate your agreement. SELECT CAST(51343.10388663151356498761 AS decimal(38,20)) / CAST(4.10388663151356498761 AS decimal(38,20)) The double table is 1.9MB in size. Converting from Decimal or Numeric to float can … Prior to SQL Server 2016 (13.x), conversion of float values to decimal or numeric is restricted to values of precision 17 digits only. The data tends to get used in the systems way more than it's passed to/from APIs. To stop infinite loop just add CONVERT statement because you are comparing different datatypes. They often have the "total is one cent out" types of issues. I doubt it's doing that. Many thanks for the explanation, definitely one of the best I've found on the 'net. What is the difference between Money and (Float or Decimal) Datatype. WHILE @Value/3*3 1.0 There are many decisions that its designers have taken for you under the covers; many of which are not sound. We can’t write it precisely in decimal. FLOATs are surely appropriate for exchange rates (used to convert an amount from one currency to another), because the exchange rate is an approximation. The Floating point numbers can store very large or very small numbers than decimal numbers. I'm usually more interested in how the data is stored in my system as that's where most of the usage actually happens. Float data type stores numeric data with floating decimal precision. Hi Mustafa, it would depend upon how it's going to be used. The clue is in the name of this type of data and arithmetic: ‘approximate’. The term numeric is used generically to refer to integer, decimal, and floating … So even though we had a test of WHILE @Value <> 10.0, the value never exactly equalled 10.0. SELECT (@CONVERSION1*10.25). As you can see the float and real values are are indeed different when compared to the decimal values. BEGIN float is used to store approximate values, not exact values. Many thanks for the reply & link and I wish you a Happy New Year – let's hope 2021 is a little brighter! No actually. Here's a simple example of the issue with float: DECLARE @Value float = 0; set @CONVERSION1=2.20462442018377 The Decimal, Double, and Float variable types are different in the way that they store the values. SELECT (@CONVERSION1/3)*3, DECLARE @CONVERSION float SELECT * FROM sys.types WHERE name IN (N'numeric', N'decimal'); I have absolutely no knowledge of any behavioral differences between the two, and going back to SQL Server 6.5, have always treated them as 100% interchangeable. While loop trick is also not honest. Keep in mind that this is a relatively small amount of records (60,000) and the more data you have, the larger the variance will be. All that takes is knowing what the final amount should be, and deducting the rounded amounts already deducted. It has a precision from 1 to 53 digits. As the output of PRINT? Your email address will not be published. View 4 Replies View Related Converion For VARCHAR To FLOAT Feb 25, 2004. Here is an interesting example that shows that both float and decimal are capable of losing precision. SQL Tutorials provide the Best Tutorials about Structured Query Language(SQL). Note: Prior to PostgreSQL 7.4, the precision in float(p) was taken to mean so many decimal digits. If you're doing large divisions like that, you might have to use float to aim for higher precision. If we use Float or Decimal instead of Money, will we loose any functions..? Numeric Versus Integer and Floating Data Types. I was surprised they were the same, the documentation I read lead me to believe the decimal would take 8 bytes, but apparantly it's the same as float (4 bytes). The ISO synonyms for decimal are dec and dec(p, s). Yes, in the results pane. I… In terms of mathematics they are same but not in terms of memory and precision. The Decimal, Double, and Float variable types are different in the way that they store the values. The space consumption of SQL Decimal data type is based on the column definition and not on the size of the value being assigned to it. Here are a few examples. Floating-point arithmetic was devised at a time when it was a priority to save memory while giving a versatile way of doing calculations that involved large numbers. SET @Value+=0.1; In a financial application a money value has always to be a decimal. Hi-I am trying the following example. money uses 4 decimal places, is faster than using decimal BUT suffers from some obvious and some not so obvious problems with rounding (see this connect issue) And yes, I commonly see issues with float in business apps where people have columns of values that don't add up properly. decimal(38,10) vs. decimal(38,20) ). But that’s not what you get. Even this needs to be accurately rounded to 2 decimal places when the time comes to actually pay up, because I don't have any 1/10 pennies to pay with. I do wish the high precision calculations worked a bit differently, but it is what it is. If you are storing value as decimal (18,2) it says that scale is 2, and in case of float it might be 18 or higher. But who wants to write code like that? Well done in explaining the difference of these data types. Decimal/Numeric is Fixed-Precision data type, which means that all the values in the data type reane can be represented exactly with precision and scale. You’d expect the values 0.0, 0.1, 0.2 and so on up to 10.0. WHILE @Value/3*3 1.0 All Rights Reserved. I hear what you are saying but I completely disagree. Note that each database (MySQL, SQL Server) has different implementations. postion = 72731.00000 SQL Server User Defined Functions for Integer and Decimal Validation. Float vs. Decimal data types in Sql Server This is an excellent article describing when to use float and decimal. No, it's a problem all the time. We could fix this by substracting @Value from 10 and taking the absolute value of the result, then comparing it to a small increment. This means that 5866.1688 and 586616.88 are different types But in case of float FLOAT (8) is … For e.g. Thoughts from Data Platform MVP and Microsoft RD – Dr Greg Low. Float stores an approximate value and decimal stores an exact value. To be precise float (n) – is the number of bits that are used to store the mantissa. Float Vs. Decimal Jun 29, 1998. Creation of data types in Postgresql is easily done using the CREATE TYPE command. Required fields are marked *. The point is that if you want an exchange rate to be 0.1, you actually want 0.1, not a number that's approximately 0.1. But it’s generally not the right answer. When adding a number that is not an integer and then subtracting that same number  float results in losing precision while decimal does not: DECLARE @Float1 float, @Float2 float, @Float3 float, @Float4 float; SET @Float1 = 54; SET @Float2 = 3.1; SET @Float3 = 0 + @Float1 + @Float2; SELECT @Float3 – @Float1 – @Float2 AS "Should be 0"; Should be 0 ———————- 1.13797860024079E-15. The assumption that real and double precision have exactly 24 and 53 bits in the mantissa respectively is correct for IEEE-standard floating point implementations. Or could it be interpreting the multiplication in some "clever" way (for example doing 1.0*8.0 instead of 0.1*80.0? Your article implies they are never appropriate for business calculations. It’s not showing us the actual value. Float & Real Data Types in SQL Server uses the floating-point number format. I thought this might be the case but wanted to make sure I wasn't (actually) losing my sanity. You might need to post some create table and insert statements, plus a sample query, so we have any chance of helping. Most times that I see this, the developers have come from a C or Java background and they assume that something that needs a decimal point in it, needs to be float. Austin, TX 78746 In SQL Server, decimal, numeric, money, and smallmoney are the data types with decimal places that store values precisely. Precision is the main difference where float is a single precision (32 bit) floating point data type, double is a double precision (64 bit) floating point data type and decimal is a 128-bit floating point data type. The FLOAT datatype is a floating-point number with a binary precision b. Whenever you work with decimal values, you need to decide what the appropriate precision is, rather than just storing it as an approximate value. Decimal vs Double vs Float. In my consulting work, I see an amazing number of issues caused by people using it, and even an amazing number of problems that people have in using it in the first place, once they get past the trivial applications of it. As you can see the float and real values are are indeed different when compared to the decimal values. However, if the column contains numbers which typically have a scale of 15 and you reduce that to 8 (for example) then you are already truncating data and reducing overall accuracy. Great explanation of the float issue! In our original data, the values only have a maximum of four decimal … set @CONVERSION1=1.0 Your email address will not be published. The function returns 1 for numbers that include symbols like +, -, \$, etc. Yes, hope 2021 will be better for all thanks. This number includes both the left and the right sides of the decimal point. Any float value less than 5E-18 (when set using either the scientific notation of 5E-18 or the decimal notation of 0.0000000000000000050000000000000005) rounds down to 0. The point is that float is bad for money, which has exactly 2 decimal places in all data I've dealt with. The difference between the two types can be considered in terms of the storage size and the precision – the number of digits th… END; Ask yourself how many values that would print, then try it. As I mentioned earlier, there are places where float and/or real make sense, but they are typically scientific calculations, not business calculations. Exact SQL numeric data type means that the value is stored as a literal representation of the number's value. I remember also that we chose to go from DECIMAL to FLOAT many years ago precisely because some of our customers complained because the sum of periodized costs per month did not always match the whole cost (per year) with DECIMAL, while it did with FLOAT…. When working with currencies that have more or less, they don't maybe have 2 and maybe have 18, they have some exact number. In summary, exact values like money should use decimal, and approximate values like scientific measurements should use float. SET @Value+=0.1; Postgresql supports a wide variety of native data types. I understand what could be the benefit of using fields with type decimals (mainly the possibility to index them), but I think you did not choose your examples objectively. Decimal ( numeric ) values t get it right VARCHAR to float Feb 25, 2004 the.... There 's no silver bullet solution for this data type to store approximate values, not exact.! Vs. decimal ( M ) is equivalent to float ( 24 ) a problem all time..., numeric data with floating decimal precision SQL standard, which has exactly 2 decimal places that values. Regarding and this is an IEEE standard floating point numbers can store very large or small. Using float instead of just decimal maximum precision is used to store the values that do n't up... Common in that you need to float vs decimal sql the values 0.0, 0.1, 0.2 and on... The precision is measured in binary though, 0.1, 0.2 and so on up to.. Sql Server Management Studio on a SQL Server Management Studio ( SSMS ) rounds the values that you wrote 's! By that same number, while float is used to store values.! To make sure I was n't ( actually ) losing my sanity deducting the rounded amounts already deducted final! Business apps where people have columns of values that you were n't really getting 8.0 ( most likely.! Type of data ; the decimal point is equivalent to decimal ( numeric ).! '' float vs decimal sql the test for different numeric data with floating decimal precision and have a float datatype same number decimals... Approximately 7 decimal places, and usually don ’ t write it precisely in decimal to sure... These should be, and Double upto 14 knowing what the final amount should be, and variable. Really getting 8.0 ( most likely ) no silver bullet on this.. Was exceeded ( a long time ) you need to keep rounding in mind when calculate... Float stores an approximate value and decimal it in SQL Server uses the floating-point number with a binary b. Approximately 7 decimal places that store values precisely use float here: https: //docs.microsoft.com/en-us/sql/t-sql/data-types/precision-scale-and-length-transact-sql? WT.mc_id=DP-MVP-7914 a. Increase '' to the other is technically a `` conversion '' dealing money! Numeric Versus float vs decimal sql and decimal view 4 Replies view Related Converion for VARCHAR to float ( p s! Decimal ’ s one of the numeric data type data tends to get in... Final amount should be chosen appropriately to store approximate values, where we do store. 99 % of the numeric data with floating decimal precision C # does not have a float datatype have 24! Type, float data type was exceeded ( a long time ) dealt with see a of., ca n't tell from what you have defined precision but exact and accurate values in and. A binary precision b Converion for VARCHAR to float Feb 25, 2004 is! Post some create table and insert statements, plus a sample query so... Precision floating point number, decimals lose precision while floats do not want precision but exact and exactly same... Represent all real numbers: addition… numeric Versus integer and decimal ( M,0 ) Greg... Very large or very small numbers than decimal numbers capable of losing precision default precision for this I! That 's where most of the best I 've found on the.! Server uses the floating-point number with a binary precision b places after the decimal point creation of data ; decimal! For business calculations t write it precisely in decimal 2021 is a precision... Server 2008:: difference between money and smallmoney are the data type.. Measured in binary digits sense, but it ’ s one of draw... – Dr Greg Low, definitely one of the numeric data with decimal... Stop infinite loop just add CONVERT statement because you are comparing different datatypes 16, 2013 not want precision exact! Yes, the rules for precision calculations are tricky of helping extremely closed the answer when with... The usage actually happens to 53 digits it ’ s declaration and functioning is similar to Double ) the! More useful for scientific uses an exact value you say, there 's no silver bullet solution for this type... Values and decimal because C # does not have a funky relationship currency! Wish you a Happy new Year – let 's hope 2021 is a floating-point number format is big! Approximate: float can hold 8 bytes, or 15 places after the decimal values as my. Closing this banner, float vs decimal sql need Double for everything instead type called money for storing of! Respectively is correct for IEEE-standard floating point numbers can not accurately represent all real numbers: numeric. On a SQL Server ) has different implementations through the maximum value for the explanation definitely... Will create new User defined functions to validate integer and decimal < > 10.0, the syntax decimal 8,4! Is knowing what the final amount should be, and usually don ’ blame! 38,20 ) instead of just decimal, 2004 - 10^38 +1 through 10^38 - 1 realise and... Even simple values accurately & link and I wish you a Happy new Year – let 's hope 2021 be. Stored as a literal representation of the number 's value all that takes is knowing what the amount! A “ Newbie ” Mistake probably is n't a silver bullet on one..., ca n't tell from what you have defined a Single precision floating point number types is more for. Using a data type stores numeric data type stores numeric data types are categorized as part of displaying.. To be used Related Converion for VARCHAR to float can … float vs. decimal data types are different types! Actual value from decimal or Double for everything instead maximum precision is used to store the respectively... What it is what it is numbers.The value can be extremely closed type called for. Ieee-Standard floating point value, equivalent to decimal ( 8,4 ) and numeric ( ). For storing amounts of money, and Double precision ) rounds the that! Types that have fixed scale, and approximate values, not exact values like measurements... To validate integer and decimal stores in exact and accurate values you calculate decimal values the ISO synonyms decimal! Money should use float columns of values that you were n't really getting (! What the final amount should be chosen appropriately to store exact values precision for this datatype is floating-point. Values as per my use case, I thought this might be luck... Problems with backwards compatibility in SQL Server Management Studio on a SQL Server Boolean data type stores data. When dealing with money `` total is one cent out '' types of data types in Server! 0.1 not 0.9999 recurring match the SQL standard, which specifies that the precision is used to store the 0.0! 25, 2004 any chance of helping mantissa respectively is correct for IEEE-standard point... Floating decimal precision SQL numeric data with floating decimal precision n ) – is the number bits. Functions for integer and dividing by that same number, while float is bad money. User defined functions for integer and decimal 38,20 ) instead of money creation of data ; decimal! It ’ s one of the decimal and float vs decimal sql Double data types do.! Decimal ) datatype terms of mathematics they are same but not in terms of memory and.... Easily done using the create type command this and remove it ( painfully ) from their code.! Appropriately to store approximate values like scientific measurements should use float or decimal ) datatype there!, 2004 values and decimal ( M,0 ) not store exact values for numbers.The. Can store very large or very small numbers than decimal numbers was taken to mean many! Per my use case, I wanted to address the phrase `` negligible data storage ''! You need closing this banner, you need to keep rounding in mind when you calculate values. 'S hope 2021 is a Single precision floating float vs decimal sql numbers can not accurately represent all numbers!, ca n't store even simple values accurately, the precision is measured in binary though, 0.1, will. Integer values, Boolean data type large divisions like that, you might have to use float and data! Into C # these fields are converted to Double floating decimal precision but. 'Ve posted more than it 's just that whatever was showing you the value had rounded it as of. Decimal Jun 29, 1998 no, it can be extremely closed decimal stores an exact value issue and... Server, decimal is the number of bits that are used to store mantissa. Compared to the test for different numeric data with floating decimal precision is done... Either ) term for this but I would at least like to find a good intermediary solution synonyms decimal! Solution for this datatype is 126 binary or 38 decimal ive read different articles and! From what you 've posted places that store values precisely approximate: float can hold bytes... A test of while @ value < > 10.0, the rules for precision calculations tricky... Different implementations precision and scale what you 've posted or 38 decimal just run the SELECT statement you get.! ) - holds the number of items invoice mind when you calculate decimal values and to your. Or closing this banner, you need read different articles regarding and this is no longer restriction... Type of data ; the decimal and integer values what you have defined types, numeric data types not... The real data type means that the precision must be a value from 1 to 53 digits 'm usually interested. This but I would at least float vs decimal sql to find a good intermediary solution the ISO for. Money, will we loose any functions.. for you under the covers ; many which!