Head of Database Migration Department, Ispirer Systems
In recent years, the amount of data in organizations has grown exponentially. In order to effectively manage gigantic and rapidly growing data sets, you need to choose the right tools to work with them.
First of all, this concerns databases. Choosing a wrong database can cause problems like inefficiency, data loss, and missed chances. So it is crucial to single out the most suitable tool for efficient data management.
Transactional databases are the most common data stores. But what are their features? How do they differ from analytical ones? What are some examples of cool transactional databases? We will talk about all this in this article.
Transactional database: How does it work?
A transactional database is a system that can efficiently and securely handle a large number of transactions. It stores data generated from interactions between two or more entities, with each interaction referred to as a transaction.
Transactions comprise fundamental database operations such as writing, reading, updating, and deleting data. Typically, a single transaction involves a series of these operations working together to accomplish a specific business task.
What are the entities involved in executing a transaction?
They can include a DBMS, data warehouse, SaaS tool, human user, automated process, stored query, web application, ETL pipeline, or any other entity capable of interacting with the data.
Why are transactional databases so cool?
A number of benefits of transactional databases include:
- Data integrity and consistency. Through the use of ACID (Atomicity, Consistency, Isolation, Durability) properties, transactional databases ensure that all transactions are processed reliably, maintaining data integrity and consistency even in the event of system failures.
- Concurrency control. They manage multiple users accessing data simultaneously. They ensure transactions are completed smoothly to prevent conflicts and maintain accuracy.
- Low latency. Transactional databases are built to handle production systems efficiently, excelling at operations that need to be completed in milliseconds.
Transactional databases: Examples
We've delved a little into theory so far. Now, let’s move on with transactional databases further.
MySQL
MySQL is a popular open-source database system known for its strong performance in handling transactions. It emphasizes efficiency and reliability, even if it sometimes diverges from strict SQL standards.
Major corporations like Netflix, Facebook, and Twitter rely on MySQL for their transaction handling needs. The platform is known for being user-friendly and scalable, making it suitable for small and large projects. It is easy to use and scale. This makes it a good choice for a variety of project sizes.
MySQL’s extensibility is another key feature, supported by a vibrant community that continuously develops extensions, plug-ins, integrations, and comprehensive documentation. This community-driven innovation ensures that MySQL remains adaptable and robust, meeting diverse user requirements and evolving technological trends.
PostgreSQL
PostgreSQL is a free and open-source database system. It handles transactions differently from regular SQL databases. It utilizes BEGIN and COMMIT statements to encapsulate transactions and provides a dedicated ROLLBACK statement for undoing changes.
Businesses choose PostgreSQL because of its advanced features. These features include multi-version concurrency control, point-in-time recovery, nested transactions, and asynchronous replication. These features make it a robust choice for transactional database needs.
Moreover, PostgreSQL has seen increasing adoption in cloud-based environments, with several new vendors offering innovative PostgreSQL-as-a-service solutions. This has further enhanced its appeal, providing flexibility and scalability for modern applications.
If your transactional database doesn’t correspond to your business requirements, database migration may appear the best solution. Whether you are planning a MySQL migration or PostgreSQL transition, it doesn’t necessarily require a long period of time to implement transition from one database to another. Most of the database transitions can be automated so it saves both time and money.
Use cases for transactional databases
Transactional databases are the backbone of many modern applications, ensuring data integrity and reliability. Here are key use cases:
- Banking systems. Banking applications use transactional databases to ensure accuracy and consistency of financial transactions. For example, they handle countless transactions daily, from deposits to withdrawals, and ensure that each one is accurately recorded.
- E-commerce platforms. E-commerce applications use transactional databases to process orders and track inventory. For example, you can use a transactional database to process a customer’s order or to track the number of items in stock.
- CRM systems. Store and manage customer data, tracking interactions and sales activities efficiently.
- Online reservations. Facilitate bookings for hotels, flights, and events, ensuring each reservation is unique and confirmed.
- Healthcare records: Maintain patient information, treatment histories, and appointment schedules with high security and accuracy.
- Supply chain management. Monitor the movement of goods from suppliers to customers, keeping data synchronized across various checkpoints.
- Government systems. Manage critical data for services like tax collection, social security, and public records.
- Logistics and transportation. Coordinate shipments, track deliveries, and manage fleet operations, ensuring timely and efficient service.
Transactional vs. Analytical
Analytical databases, often called OLAP databases, are designed for processing complex queries and analyzing large datasets. These databases are great for tasks that involve reading a lot of data. They support business intelligence, data mining, and reporting applications, helping organizations gain insights and make better decisions. Conversely, transactional databases, or OLTP systems, are optimized for handling numerous quick transactions per second, focusing on speed and efficiency.
The structural differences between these databases are significant. Analytical databases typically use denormalized schemas, where data is duplicated across multiple tables to streamline and accelerate queries. In contrast, transactional databases employ normalized schemas to minimize data redundancy and ensure data consistency. This structural choice reflects their primary functions: analytical databases are built for fast query performance, while transactional databases are designed to maintain data integrity.
Analytical databases are important for business intelligence and data warehousing. They process a lot of data to uncover insights and trends that help with strategic decision-making. Key distinctions between the two types of databases include:
- Data. Transactional databases manage detailed and current data, while analytical databases handle historical and summarized data.
- Structure. Transactional databases are normalized to reduce redundancy and enhance integrity, whereas analytical databases are denormalized for quicker query responses.
- Operations. Transactional databases are optimized for write operations, while analytical databases are optimized for read operations.
- Users use. Transactional databases for daily operations and front-end applications, while analytical databases are used by analysts and decision-makers for strategic purposes.
Analytical databases involve:
- Column store
- Calculating complex aggregate functions
- Read-only queries and batch-write loads
- Complex queries
- Ad-hoc, non-routine analyses
Transactional databases involve:
- Row store
- Operating on one “object” at a time
- CRUD operations (Create, Read, Update, Delete)
- Precisely managing the state of a database
- Supporting many operations per second with high throughput
Let’s wrap up
In today’s dynamic business landscape, the choice of a transactional database can significantly impact your operations and efficiency. Whether you're using MySQL, PostgreSQL, or another system, it's essential to ensure that your database meets your specific needs. If you find that your current transactional database is not up to the task, migrating to a better solution is always an option.
Tools like Ispirer Toolkit can facilitate a seamless database migration, ensuring that you can optimize your database environment without compromising on performance or reliability. With the right database in place, your business can achieve greater efficiency, scalability, and success.
