How can you write SQL queries that work on any database?

Definitely ANSI works in most of the databases also you can create your own function or data type to use in any of the database, that works more accurate to serve your business.

Writing an SQL query that can work on any database is not a trivial task, as different database systems may have different syntax and features. However, one possible way to achieve this goal is to use the Core SQL standard, which specifies the minimum requirements for what a database engine should support in terms of SQL syntax. Core SQL is defined by the international standard ISO/IEC 9075:2023, which consists of 9 parts. You can find the details of each part on the ISO website. To write an SQL query using Core SQL, you need to follow the rules and conventions specified in the standard, and avoid using any vendor-specific extensions or features that are not part of the standard.

Use this Standard: ISO/IEC 9075:2023 (ANSI X3.135). Anyway, IMHO, do not use the peculiar potential of each DBMS is a pity...

I agree but their is also a thing is the syntax we should be using the ANSI BUT try also to write the query in standard sql syntax not based on any provider specific most of them support standard sql

Following ANSI SQL standards is crucial for writing portable SQL code. Consistency in data types and formats is also essential.

I agree that cast should work but the standard data type also works like if you use date it’s widely accepted and if use the case it will automatically casted to the required data type

- Using standard data types like VARCHAR, INTEGER, DATE, and BOOLEAN instead of database-specific types, could be more likely to be consistent across different databases. - Explicitly defining column lengths may help. Different databases may have different default values for string length or numeric precision.

Yes I totally agree on this and we should always use the functions that are widely accepted across all platforms and venders to that it’s portable and easy to use

Always try to design your table schema based on your queries . Try to make your select queries fields as part of Primary and Composite Keys , so that your select queries (READ operations) will be faster . Also based on the key indexes partitions will be well defined and WRITE operations will be faster . Both READ and WRITE operations performance are depends on schema design

In my experience here is the few things you can do - only query the required data never do select * - use proper indexes - simplify you queries - see the execution plan and verify the issues

To optimize SQL queries for cross-database compatibility, we should focus on writing efficient and readable code that adheres to ANSI SQL standards. We can avoid vendor-specific extensions and ensure consistent handling of data types and formats. Using portable functions and operators for common tasks and rigorously testing and debugging our queries across various database platforms should help. By prioritizing compatibility and performance in SQL codes, we can ensure it runs seamlessly on any database system.

I would suggest to use a cross platform tools for that as their are many available easily and are free as well like azure data studio etc or visual studio code

1. Regarding the joins, always use standard ANSI format i.e. INNER JOIN, LEFT JOIN, RIGHT JOIN and FULL OUTER JOIN, instead of + which is used in Oracle PLSQL. 2. As this article is on compatibility of SQL Queries in different platforms, try to use generic ANSI functions, and for complex operations, use self defined functions. For example, QUALIFY function is available in some platforms like Teradata, Snowflake only but not present in other platforms like Oracle, PostgreSQL, MySQL SQLite etc. So, to make the query compatible, avoid using such functions. 3. For performance improvement, use the joins effectively. Try not to use EXISTS and NOT EXISTS functions. Use LEFT JOIN instead. 4. Do not use unnecessary string functions like Upper

Be sure you understand why you want to do this. Using an vendor specific syntax or query, which does not need to go through "translation layer" are often faster than their standard counterparts. Using specialized index types, or vendor specific constraints may perform better for your workloads. Examples on where you might need to stick to standards are: 1) you are doing some extension, that will be attached directly to some application that is multiplatform, and you have no idea what will be actual database used, and don't want to limit your customers. 2) you do some application that will be helping customers understand their database, some monitoring or auditing software. 3) you prioritize vendor independence over performance.