# Decimal vs. Numeric

## What's the Difference?

Decimal and Numeric are both data types used in programming languages to represent numbers with decimal points. However, there are some differences between the two. Decimal is a fixed-point data type that allows for precise decimal arithmetic and is commonly used in financial calculations where accuracy is crucial. It can store up to 38 digits, making it suitable for handling large numbers. On the other hand, Numeric is a variable-length data type that can store both integers and decimal numbers. It offers a balance between precision and storage size, as it can store up to 131,072 digits before the decimal point and up to 16,383 digits after the decimal point. Numeric is often used in scientific and engineering applications where a high degree of precision is required.

## Comparison

Attribute | Decimal | Numeric |
---|---|---|

Definition | A data type that represents decimal numbers with fixed precision and scale. | A data type that represents numeric values with variable precision and scale. |

Precision | Fixed precision is specified when defining the column. | Variable precision can be specified when defining the column. |

Scale | Fixed scale is specified when defining the column. | Variable scale can be specified when defining the column. |

Storage Size | Storage size depends on the precision and scale specified. | Storage size depends on the precision and scale specified. |

Range | Can store numbers with a maximum precision of 38. | Can store numbers with a maximum precision of 38. |

Usage | Commonly used for financial calculations and monetary values. | Commonly used for mathematical calculations and general numeric values. |

Exactness | Decimal values are exact and do not lose precision. | Numeric values can lose precision due to rounding. |

## Further Detail

### Introduction

When working with databases, it is essential to choose the appropriate data types for storing numerical values. In many database management systems (DBMS), two commonly used data types for representing decimal numbers are Decimal and Numeric. While these two data types may seem similar at first glance, they have distinct attributes that make them suitable for different scenarios. In this article, we will explore the similarities and differences between Decimal and Numeric, shedding light on their various attributes and use cases.

### Definition and Precision

Both Decimal and Numeric are fixed-point data types that store decimal numbers with a specified precision and scale. The precision refers to the total number of digits that can be stored, while the scale represents the number of digits to the right of the decimal point. For example, a Decimal(10, 2) can store up to 10 digits, with 2 digits after the decimal point.

One key difference between Decimal and Numeric lies in their precision handling. In some DBMS, Decimal is considered a synonym for Numeric, and both terms are used interchangeably. However, in other systems, Decimal is a distinct data type that allows for greater precision than Numeric. For instance, Decimal(38, 10) can store up to 38 digits, while Numeric(38, 10) may be limited to a lower precision.

### Storage Space

Another important aspect to consider when comparing Decimal and Numeric is their storage space requirements. Since both data types store fixed-point decimal numbers, they consume a fixed amount of storage space regardless of the actual value being stored.

The storage space required by Decimal and Numeric depends on the precision and scale specified. In most DBMS, Decimal and Numeric use a byte-based storage mechanism, where each digit requires a certain number of bytes. For example, in some systems, a Decimal(10, 2) may require 5 bytes, with 4 bytes for the integer part and 1 byte for the fractional part. However, it is worth noting that the actual storage space allocation may vary across different DBMS implementations.

### Arithmetic Operations and Precision

When performing arithmetic operations on Decimal and Numeric values, it is crucial to consider the resulting precision and scale. Both data types handle arithmetic operations differently, which can impact the accuracy of calculations.

Decimal arithmetic operations typically preserve the precision and scale of the operands. For example, adding two Decimal(10, 2) values will yield a result with the same precision and scale. On the other hand, Numeric arithmetic operations may require explicit casting or result in a loss of precision. For instance, adding two Numeric(10, 2) values may result in a Numeric(11, 2) value, requiring additional storage space.

It is important to note that the behavior of arithmetic operations may vary across different DBMS implementations. Some systems may automatically adjust the precision and scale, while others may require explicit casting or provide configurable options to control the behavior.

### Comparison and Sorting

Decimal and Numeric values can be compared and sorted based on their numerical values. When comparing Decimal and Numeric values, the precision and scale are taken into account to ensure accurate results.

However, it is worth noting that the comparison and sorting behavior may differ across DBMS implementations. Some systems may consider Decimal and Numeric as distinct data types, requiring explicit casting for comparison. Others may treat them as interchangeable, allowing direct comparison without casting.

When sorting Decimal and Numeric values, the precision and scale are crucial for determining the order. For example, a Decimal(10, 2) value will be sorted differently from a Decimal(10, 4) value, even if their numerical values are the same. The precision and scale dictate the level of granularity in the sorting process.

### Use Cases

Decimal and Numeric data types find applications in various scenarios, depending on the specific requirements of the data being stored.

Decimal is often preferred when dealing with financial calculations, where precision is of utmost importance. For example, when storing monetary values or performing complex financial calculations, Decimal provides the necessary precision to avoid rounding errors and maintain accuracy.

Numeric, on the other hand, may be suitable for scenarios where precision is not as critical, and storage efficiency is a priority. For instance, when dealing with large datasets or performing statistical calculations, Numeric can provide a balance between storage space and accuracy.

### Conclusion

Decimal and Numeric are two fixed-point data types commonly used for storing decimal numbers in databases. While they share similarities in terms of precision and scale, they have distinct attributes that make them suitable for different scenarios.

Decimal offers greater precision and is often preferred for financial calculations that require high accuracy. Numeric, on the other hand, provides a balance between precision and storage efficiency, making it suitable for scenarios where precision is not as critical.

When choosing between Decimal and Numeric, it is essential to consider the specific requirements of the data being stored and the behavior of the DBMS being used. Understanding the attributes and differences between these data types will help ensure accurate and efficient storage and calculations in database systems.

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