Last Updated on November 25, 2023 by Hina Rubab
Operational Database or otherwise called On-Line Transaction Processing (OLTP), is the database management system where your enterprise data is stored and accurately processed for real-time needs. These systems also offer analytical capabilities for real-time analysis of data. These operational database models are highly sought after and can effectively manage both the conventional relational SQL databases and even the NoSQL databases.
OLTP are also extending their support to the distributed databases to offer increased availability, better scalability, and higher fault tolerance. Some of the classic examples of Operational Databases are:
- AWS Dynamo
- Microsoft SQL Server
- Apache Cassandra
- MongoDB, etc.
Table of Contents
What is the need to consider operational database Management?
Suppose if a database handles the data for a shoe seller business with a global process. From warehouse data like all inventories or raw materials, WIP goods, and the products are maintained, it will help the purchasing team located at a different geographical location to know about the next order quantities instantly.
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From the company’s financial data and manufacturing, production, sales, and marketing, CRM data, everything can be handled by an ideal Operational DBMS. This will help the users to quickly analyze data and insights in real-time and also benefit from the most advanced and complex analytical tools that come with it.
Considering all the given needs and offerings, operational DBMS has lately become very popular for the following reasons.
- Analytical Abilities: operational databases can offer better analytical abilities in real-time to assist in decisionmaking. It can also incorporate different applications to enhance analytical skills based on different user needs and without changing the database’s given state.
- IoT and Big Data: operational databases also help to harness better the optimum potential of Big Data and IoT applications. This is made possible with the help of real-time monitoring and review and offering many apt big data solutions on its own. Hadoop, along with Mongo DB and Cassandra, can help unveil the fullest potential of Big Data applications.
- Better fault Tolerant: By operating in a distributed database model, operational databases can be more fault resistant. With a distributed model, even when one of the components or an entire site goes down or malfunctions, it will not affect the rest of the system and the database.
- More scalability: The latest operational DBMS are all-set to scale out based on the users’ requests anytime. With the add-on advantage of low latency and high concurrency, the business can adopt a more cost-effective pay as you use principle.
Operational database system functions
Let us now explore the functional features of operational DBMS
Cataloging and indexing
The primary function of operational DBMS is effective Indexing and cataloging, which will increase the efficiency of data storage and easy retrieval. Indexing is done more effectively with primary, secondary, and clustered indexes. With cataloging, a file’s critical attributes are added to it, which can be used to recall it later quickly.
Putting it simply, replication refers to making a true copy of the data or file as a whole by reflecting the same at multiple locations. This is critical in the distributed systems in which the same data is stored across various locations and can be instantly and easily accessed with consistency.
File storage and structure
Another crucial function in terms of enterprise database management is file storage. This is another major thing that makes operational databases more popular as functional DBMS cases are more complex. To serve this purpose, the system should be robustly built as being capable of storing files at the most relevant locations. Some of the best organization systems to serve this purpose are Sequential, Hash, Heap, Clustered file organization system, etc.
Query processing Management
Operational databaseshave better analytical capacities due to the superior query processing algorithms it uses. Query processing is not a standalone process, but in database scenarios, it represents the end-to-end process starting from translating the query by the users into simpler low-level instructionsto the optimization and analysis of the question to process. At the end of this process, they will extract the most relevant data from the given database and present it to the user. With operational DBMS, all these tend to happen in milliseconds.
Transactional support Management
Transaction systemsare considered as logical unitsof the operational DBMS. It is highly important to make this work consistently and ensuring necessary recovery services. The process of transaction support effectively dealswith it and makes the system ACID-compliant. This means three factors are ensured as the:
- Atomicity, which distinguishes a single transaction from others
- Consistency to ensure that the transactions which change the database during the query process do not ultimate make it inconsistent
- Isolation to keep the transactions independent in the concurrent state, and
- Durability ensures that the transactions are stored permanently in the datasets along with the results of the process
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Advantages of Operational DBMS Management
- Operational DBMS are highly versatile and can accommodate the distributed systems as SQL, NoSQL, and even the latest New SQL databases.
- Operational systems are highly available, highly scalable, and more fault-tolerant.
- Operational database management systems are highly secured too, with
- built-in encryption support
- Auditing functions
- Cyber-attack protection etc.
- Operational database management systems are very flexible and can work effectively with multiple applications simultaneously.
- These systems are oftenmore economical than other available systems.
Disadvantages of Operational DBMS
- These systems seem to have a larger learning curve where the users need to get comprehensive training to manage the operational DBMS.
- The installation process of operational databasesrequires more time and effort to set up optimally.
- Security may also be a concern since the data gets stored in remote locations where the overall control of the same may be difficult.
In conclusion, despite a few disadvantages too out there, there is no denial that operational database management systems are highly efficient in managing all database handling requirements of an organization. Most of the Fortune 500 enterprises are already using this approach to their DBMS management. By knowing the architecture and features of operational databases, you can also explore whether it is the right solution for your enterprise database management needs.