SQL has been gaining in popularity and importance for the past two decades. As this programming language allows users to perform various operations with databases, the future of SQL is an important topic. With the further AI development and issues such as Big Data, the relevancy of SQL becomes questionable. More about the SQL's future, its main features and threats you can read further in this article. You can also read more about the difference between SQL and SQL Server and what you can do with either of them.
Why use SQL?
SQL is a programming language that has been created to facilitate communication between organizations and their relational databases. By using SQL you can retrieve, sort, access, and update information very quick and easy. See below what you can do with SQL:
- Create and manage databases: using SQL, you can manage and generate new databases.
- Unite data from different places: Data is usually stored in different places such as multiple tables. With SQL you can use a specific function that conjoins these tables so they can create answers for more complex issues
- Creating data reports: You can structure different outputs into a consistent report to which others have access. This simplifies the overall analysis communication and interpretation which further contributes to a more argumented decision making.
- Explore data: SQL allows you to get access to certain data within different databases.
Difference between SQL and SQL Server
Although SQL and SQL Server sound similar, there are multiple differences between them. The main difference is that SQL is a query language that is meant to produce certain orders so relational databases can be specified, whereas SQL Server is a database management system that conducts these SQL queries.
Another difference is the fact that SQL Server has updates whereas SQL does not. SQL doesn’t come with any updates because all SQL-coded queries within the database will always remain the same. By contrast, SQL Server does have updates because users actually own these licenses. Therefore, Microsoft revises them regularly which leads to updates.
A third difference between SQL and SQL Server is related to the platform. As mentioned above, SQL queries remain a constant, therefore, the language can be used on every device and every operating system. However, since SQL Server is not an open source, the license can’t be put to use on all systems and is therefore dependent on the platform.
Main purpose of SQL Server 2022
One of the main purposes and biggest benefits of SQL Server 2022 is the possibility to make use of hybrid solutions. For example, with SQL Server 2022 you can create a connection with Azure Synapse Analytics through the feature Azure Synapse Link. This way you do not need to replicate or move data to gain a clear insight to you SQL Server 2022 databases. Additionally, with Azure Synapse Link you can connect SQL Server 2022 with Azure Synapse Analytics and gain a clearer analysis of your database.
Read more about the features of SQL Server 2022.
Artificial intelligence
With the development of Artificial Intelligence, questions like: “Will AI replace SQL?” are fair to ask. Of course, for now it’s not yet clear how far AI will come but regarding SQL there are no major concerns at the moment. Programming with SQL still requires a human touch. Human adaptation and interpretation of certain requirements is something that AI is still lacking. For this reason, AI is not a threat (yet).
For now, Artificial Intelligence can be and is beneficial for SQL programmers. Queries can be generated by AI, recurring and routine tasks can be performed by AI and database performance can be optimized in terms of efficiency. So, for now AI is more of a supportive tool for SQL programmers instead of a threat.
Big Data
SQL is a great way to work with Big Data. If your organization prioritizes security, data validity, reliability, and consistency, SQL is the right tool to use. SQL is the most compatible where relational databases are being used. Here are some tips when using SQL for Big Data:
- By labelling views and keys and removing outdated tables and columns, you can ensure consistent data.
- Do’s and don’ts are there for a reason. They shouldn’t be ignored since applying them ensures that analysis can be done more fluent. A few examples are using upper- and lowercase appropriately, following SQL execution, and applying descriptive names.
- Make sure your database erase unnecessary data. This way your database is normalized as much as possible which means it gets closer to an ACID-compliance state.
SQL: Future Predictions
Data science has been in an enormous rise for the past two decades and expectations are that this is not going to change in the near future. Scientists are determined to keep on this progress and one of the most important tools to achieve this is SQL. Since data is growing in volume, variety, and speed, SQL plays a crucial role because it allows users to analyse and, more importantly, query all this data. Additionally, the compatibility of SQL with distributed computing frameworks like Apache Flink and Apache Kafka is also a beneficial feature that contributes to processing and analysing data in an efficient way.
Another beneficial outcome of continuing using SQL is stream processing. It allows users to transform, analyse, filter or enhance data very quickly. Since data is growing like never before, being able to work with SQL is really important in certain areas of expertise and is therefore a very convenient skill to have.
Do you have questions? Contact us!
For more information about which Microsoft software and licenses are best for you, please contact us. We are available from Monday to Friday from 9 a.m. to 5 p.m.
