Introduction on SQL+

Introduction

The SQL+ programming language offers several features and capabilities that elevate it to the rank of an enterprise-worthy tool, representing a logical evolution of the SQL programming language. One of the main benefits of SQL+ is its capability to add Semantic Tags to statements using SQL through straightforward comments, opening up a world of possibilities for quickly creating reliable and effective data services.

The most common programming language for managing and modifying databases with relationships is structured query language (SQL). It has been a mainstay in the data management industry due to its efficiency and simplicity. However, the requirement for more sophisticated SQL capabilities has grown as data volumes, and complexity continues to increase at an exponential rate. A new version of SQL, or SQL+, has evolved in response to this demand, improving features and functionalities that raise the bar for data querying and processing.
We will go into the realm of SQL+ in this post and examine its features, benefits, and practical applications. We'll give you code snippets and examples to show how powerful SQL+ is when used in action, enabling you to use this complex software with ease SQL variant to tackle complex data challenges.

What is SQL+?

SQL+ represents an evolution of the traditional SQL language, incorporating additional features and syntax enhancements. It builds upon the foundation of SQL and extends its capabilities, enabling users to perform more sophisticated operations and achieve better performance and productivity. SQL+ is designed to address the needs of modern data-intensive applications, where efficiency, scalability, and flexibility are paramount.

Why we used SQL+?

SQL+ is used for various reasons, as it offers numerous advantages and capabilities that make it a valuable choice for database management and data-related tasks. Here are some key reasons why SQL+ is commonly used-

Enhanced functionality: SQL+ builds upon the foundation of traditional SQL and extends its capabilities. It introduces advanced features like window functions, advanced join techniques, and support for complex data types like JSON and XML. These enhancements provide developers and data professionals with more powerful data manipulation, analysis, and reporting tools.

Improved productivity: SQL+ simplifies and streamlines the process of working with databases. Its intuitive syntax and rich features enable developers to write complex queries more efficiently and with fewer lines of code. This leads to increased productivity and faster development cycles, allowing businesses to quickly derive insights from their data and make informed decisions.

Performance optimization: SQL+ incorporates various optimization techniques to improve query performance and resource utilization. Query hints, for example, allow developers to provide directives to the query optimizer, guiding it to choose the most efficient execution plan. This can significantly enhance query performance, particularly in scenarios where specific indexes or access paths yield better results.

Seamless integration: SQL+ serves as an effective ORM (Object-Relational Mapping) tool for integrating SQL with programming languages like C#. It provides a seamless bridge between the object-oriented paradigm of programming languages and the relational world of databases. This integration simplifies data retrieval, manipulation, and persistence operations, enabling developers to work with databases more intuitively and efficiently.

Enterprise-worthy data services: With the ability to add Semantic Tags to SQL statements, SQL+ enables the creation of enterprise-worthy data services quickly. By providing additional context and instructions to the database engine, developers can optimize query execution and build robust and scalable data services in a matter of minutes. This allows organizations to leverage the power of SQL more efficiently and effectively, delivering high-performance data solutions.

How to Add Code Snippets?

Step 1. Open SQL+  documentation and click on the top menu list on Docs.

Step 2. Download Code Snippets and extract the CodeSnippitszip file. Code Snippets.

Step 3. Copy the + folder, which is available from under the CodeSnippits folder, and paste the folder into the SQL Snippets folder, which is available from the Extract code snippets downloaded zip folder, and copy the SQL+ folder.

C:\Users\UserName\Downloads\Code Snippits\CodeSnippits

 

Paste the SQL+ folder into SQL Server Snippets folder.

C:\Program Files (x86)\Microsoft SQL Server Management Studio 19\Common7\IDE\SQL\Snippets\1033

 

Step 4. Add Code Snippets in SQL Server.

Open SQL Server and select the Tools option on the top menu bar, then select Code Snippets Manager.

In Code Snippets Manager, add an SQL+ Library.

Step 5. Download and Install Code Generator

SQL Code Generator helps to generate data services and models based on Database Tables. It's a very simple installation.

Step 6. Check whether SQL+ Code Snippets is working or not.

Semantic Tags

SQL+ Routine Tag

The routine tag is an essential component that must be included at the beginning of a stored procedure or ad-hoc query in SQL+. It serves as a signal to the builder, indicating that the routine is available for code generation. This tag also carries additional functionalities, including the definition of the select type, acceptance of comments and author name, and the ability to customize the timeout duration.

Overall, the routine tag plays a pivotal role in SQL+ by signaling its availability for code generation and enabling developers to define the select type, include comments and author name, and customize the timeout duration. By leveraging this tag effectively, developers can enhance collaboration, improve code organization, and optimize the execution of routines.

 --+SqlPlusRoutine
        --&SelectType=NonQuery or SingleRow or MultiRow or JSON or XML or MultiSet
        --&Comment=Comment
        --&Author=Author
        --&CommandTimeout=seconds
 --+SqlPlusRoutine 

SelectType: NonQuery: Indicates that the routine does not return a result set. It is typically used for operations such as INSERT, UPDATE, or DELETE statements.

SingleRow: Specifies that the routine executes a SELECT statement expected to return a maximum of one row. This is commonly used when selecting by a primary key. The result set is mapped to a single instance of a result object rather than a list.

MultiRow: Indicates that the routine executes a SELECT statement that can return an undetermined number of rows. The result set is mapped into a list of result objects representing multiple rows.

JSON: Specifies that the routine executes a SELECT statement with the FOR JSON PATH clause. The result is returned as a JSON string and mapped to a property called "JsonResult" in the result object.

MultiSet: Used with Query tags for routines that return multiple result sets. It allows for the handling of multiple sets of results within a single routine. For more information, refer to the documentation on Multiple Result Sets and Query Tags.

XML: Indicates that the routine executes a SELECT statement with the FOR XML clause. The result is returned as an XML string and mapped to a property called "XmlResult" in the result object.

Comment: This field provides an opportunity to add a comment describing the routine's purpose or functionality. It serves as documentation and aids in the transfer of knowledge between the creator of the routine and the developers using it.

Author: Specifies the name of the creator of the SQL routine. This information helps other developers quickly identify and contact the original creator if there are any questions or issues related to the routine. Optionally, an email address can be included for further contact.

CommandTimeout: Allows overriding the default timeout duration for commands in the routine. Developers can specify the maximum number of seconds for the allowed execution time of the routine. This is useful when dealing with routines that may take longer to execute than the default timeout allows.

SQL+ Parameter Validation Tags

Parameter validation tags in SQL+ are a powerful tool for ensuring data integrity and enforcing validation rules at the service layer. These tags are applied to parameters in stored procedures or variables in ad-hoc queries, enabling developers to define validation rules and constraints that must be met before executing the SQL code. By utilizing parameter validation tags, SQL+ allows developers to make their services the gatekeepers of pristine data. The validation rules specified in these tags are enforced within the service layer, acting as a safeguard against invalid or malicious data input. This ensures that only valid and reliable data is processed and stored in the database.

    --+CreditCard
    --+Email
    --+MaxLength=MaximumLength
    --+MinLength=MinimumLength
    --+Phone
    --+PostalCode
    --+Range=MinimumValue,MaximumValue
    --+RegExPattern=RegularExpression
    --+Required
    --+StringLength=MinimumLength,MaximumLength
    --+Url

CreditCard: Enforces validation to ensure that the mapped property in the generated service contains a valid credit card number.

Email: Validates that the mapped property in the generated service is a valid email address.

MaxLength: Validates that the length of the mapped property does not exceed the specified maximum size.

MinLength: Validates that the length of the mapped property meets or exceeds the specified minimum size.

Phone: Performs liberal phone number validation for the mapped property in the generated service. It can also utilize regular expressions to define custom validation rules for phone number formats.

PostalCode: Enforces liberal validation for postal codes in the mapped property of the generated service. It can also utilize regular expressions to define custom validation rules for different postal code formats.

Range: Validates that the value of the mapped property falls within the specified range of minimum and maximum values.

MinimumValue: Specifies the minimum value allowed for the mapped property.

MaximumValue: Specifies the maximum value allowed for the mapped property.

RegExPattern: Enforces validation using a regular expression pattern for the mapped property in the generated service. This allows for custom validation based on specific pattern requirements.

Required: Enforces validation to ensure that the mapped property in the generated service is required and cannot be null or empty.

StringLength: Enforces validation for the minimum and maximum lengths of the string in the mapped property.

MinimumLength: Specifies the minimum length allowed for the string in the mapped property.

MaximumLength: Specifies the maximum length allowed for the string in the mapped property.

Url: Validates that the mapped property contains a fully qualified URL, following the appropriate format.

Validation Tag with Error Message

    --+CreditCard
    --&ErrorMessage=ErrorMessage

    --+CreditCard
    --&ErrorResource=ResourceType,ResourceName

Error Message: Provides a custom error message is displayed when an error has occurred where "ErrorMessage" is the custom error.

Error Resource: Provides a custom error message residing in a resource file. It is used for saving and getting custom errors from any local or hosted directory.

ResourceType: Type of resource to utilize.

ResourceName: Type the name of the resource within the resource type.

SQL+ Return Value Tags

--+Return=EnumeratedValue,Description
    RETURN 1;

In SQL+, we return Enum values from Stored Procedure. It's very beneficial for API Call getting the result of the API Call. In a stored Procedure, we can return multiple enum values and also get those enum values from the response on the API Call.

Code Generation

Step 1. Create a .Net API Project structure

In an API project, we establish a connection string and then right-click on Solution Explorer.

And click SQL+ Builder to generate Data services.

Step 2. Write the DB connection string and click Connect

Step 3. Select Stored Procedure

Here, we select all stored procedures that want to generate data services.

Step 4. Build Services

Now click the last option from the left menu, which is build services, then click to Build Project.

 

After building the Project SQL+ Code generator, it adds a dbo folder to your Project, containing SQL Services and Models class files.

Features In SQL +

Ecosystem-Based on SQL: The database's entire potential is at your disposal. Even the trickiest SQL can be converted to an object-oriented library with ease.

Productivity: Create code by writing SQL, adding Semantic Tags, and finishing with code. You won't ever need to create SQL wrapper code again.

Semantic Tags: For SQL developers, this is a game-changer. It offers field-level parameter validation, enumerated return values, and intelligence-assisted comments and helps you to fine-tune your created services.

Value Parameters for Tables: Complete support, including type creation and parameter mapping.

Queries with multiple result set (Mars): Each record set is assigned a class and contained within a result data object.

Transient Error Management: Enables logging and adjustable retry options.

Best Practises: Adheres to the DRY and SOLID guiding principles.

Usability: Model binding and event dissemination are made easier by the created services' object-oriented design.

Support: We are here to help you achieve because when you succeed, we also succeed. Unlimited assistance is available with every upgraded subscription.

Enhanced Data Manipulation: One of the key strengths of SQL+ lies in its expanded data manipulation capabilities. It introduces advanced querying techniques, such as window functions, which allow for complex calculations and aggregations within a result set. Let's consider the following example.

SELECT
  employee_id,
  last_name,
  salary,
  RANK() OVER (PARTITION BY department_id ORDER BY salary DESC) AS rank
FROM
  employees;

In this code snippet, the RANK() function is a window function that calculates the rank of each employee's salary within their respective department. This powerful feature enables businesses to gain valuable insights into employee compensation relative to their peers, facilitating fairer compensation practices and informed decision-making.

Advanced Join Techniques: SQL+ offers enhanced join techniques that optimize query performance and provide more flexibility in data retrieval. For instance, the MERGE statement combines INSERT, UPDATE, and DELETE operations into a single statement, simplifying complex data synchronization tasks. Consider the following example:

MERGE INTO target_table
USING source_table
ON (target_table.id = source_table.id)
WHEN MATCHED THEN
  UPDATE SET target_table.column = source_table.column
WHEN NOT MATCHED THEN
  INSERT (id, column)
  VALUES (source_table.id, source_table.column);

In this code snippet, the MERGE statement efficiently synchronizes the target_table with the source_table based on the matching criteria defined in the ON clause. This feature streamlines data integration processes and eliminates the need for multiple queries or complex procedural logic.

Performance Optimization: SQL+ services execute up to four times faster than Entity Framework and nearly twice as quickly as Dapper. They also remove transpiring at runtime. SQL+ introduces advanced optimization techniques to improve query execution speed and resource utilization. It incorporates query hints, which provide directives to the query optimizer on how to best execute a particular query. Let's consider an example:

SELECT /*+ INDEX(employees employees_index) */ *
FROM employees
WHERE department_id = 100;

In this code snippet, the INDEX(employees employees_index) hint instructs the query optimizer to utilize the specified index when retrieving data from the employee's table. This guidance can significantly enhance query performance, especially in scenarios where specific indexes or access paths are known to yield better results.

Handling Complex Data Types: SQL+ extends its support for complex data types, such as JSON and XML, enabling users to query and manipulate unstructured or semi-structured data seamlessly. Let's consider an example of querying JSON data -

SELECT order_id, order_details
FROM orders
WHERE order

Conclusion

In conclusion, SQL+ stands out as a cutting-edge SQL variant that enhances the capabilities of the traditional SQL language. With the addition of Semantic Tags and its exceptional support for C# and SQL integration, SQL+ provides developers with a powerful toolset for building enterprise-worthy data services efficiently and effectively. Furthermore, SQL+ shines as an Object-Relational Mapping (ORM) tool for C# and SQL integration. It seamlessly bridges the gap between the object-oriented paradigm of C# and the relational world of SQL databases. With SQL+, developers can leverage the power of SQL queries within their C# codebase, facilitating data retrieval, manipulation, and persistence operations.

SQL+ offers a feature-rich environment that empowers developers to work with databases more efficiently. Its intuitive syntax and comprehensive toolset makes it ideal for creating data services in various enterprise scenarios. By combining the simplicity and familiarity of SQL with the flexibility and power of Semantic Tags, SQL+ provides an unparalleled ORM experience for C# developers.

FAQ's

Q1. What is SQL+?

SQL+ is a programming language that extends SQL by adding additional features, such as semantic tags and validation rules, to enhance the development of enterprise-level data services.

Q2. What are semantic tags in SQL+?

Semantic tags in SQL+ are comments added to SQL code that provide additional information, such as select type, validation rules, and author details. These tags help generate code and enforce validation at the service layer.

Q3. How does SQL+ improve data validation?

SQL+ improves data validation by allowing developers to apply parameter validation tags to parameters or variables in stored procedures or ad-hoc queries. These tags enforce validation rules for properties like credit card numbers, email addresses, or length constraints, ensuring data integrity.

Q4. Can I customize validation rules in SQL+?

Yes, SQL+ provides flexibility in defining custom validation rules using regular expressions and user-defined functions. This allows developers to enforce specific validation patterns or complex validation logic according to their application's requirements.

Q5. What is the purpose of the routine tag in SQL+?

The routine tag is a mandatory tag placed at the beginning of a stored procedure or ad-hoc query. It signals to the builder that the routine is available for code generation and allows developers to define select types, provide comments, specify authors, and customize timeout settings.

Q6. How does SQL+ enhance collaboration among developers?

SQL+ facilitates collaboration by allowing developers to include comments and author information in the routine tags. This improves knowledge sharing and documentation and aids issue resolution by providing clear attribution and contact details.

Q7. Can SQL+ handle multiple result sets?

Yes, SQL+ supports multiple results sets through the MultiSet tag. When used in combination with Query tags, it enables services to return and handle multiple sets of results efficiently.

Q8. Does SQL+ provide validation for string lengths?

Yes, SQL+ offers validation tags like MaxLength, MinLength, and StringLength to enforce constraints on string lengths. These tags ensure that the length of a string property falls within specified limits.

Q9. Can SQL+ validate URL formats?

Yes, SQL+ provides a URL validation tag that enforces the format of a fully qualified URL. This helps ensure that URL properties in the generated service adhere to the correct format.

Q10. How does SQL+ contribute to data integrity and security?

SQL+ enhances data integrity and security by enforcing validation rules at the service layer. With parameter validation tags, SQL+ ensures that only valid and trustworthy data is processed, reducing the risk of data corruption, breaches, or vulnerabilities.