Introduction to Operational Database
An Operational Database or OLTP (On-Line Transaction Processing) is a database management system where data is stored and processed in real-time. They also provide a real-time analytics opportunity which is highly sought after and can manage both SQL and NoSQL based database. They are also increasing their support for Distributed databases so as to improve on scalability, availability, fault tolerance. Some examples of Operational Databases are Microsoft SQL Server, AWS Dynamo, Apache Cassandra, MongoDB, etc.
Need for Operational Database
Imagine a Global Shoe selling business who operates out of India. From the warehouse data where all the details of inventory like raw materials, WIP Goods, finished products is maintained, this helps the Purchase team situated in some other corner of the world to know what to order next and in what quantities. From the company’s Financial Data, Production and Manufacturing data, Sales Marketing data, CRM and SCM data, etc. Everything is handled by the company’s Operational Database management system. This helps them in analyzing data and information in real time and provides advanced complex analytical tools.
Therefore, an operational DBMS has become extremely important for the following reasons,
- Analytical Abilities: It can provide the real-time analytical ability to help in any decision-making process. It can incorporate various applications to enhance the analytical abilities as per user needs without changing the state of the database.
- Internet of Things: It helps in harnessing the true potential of IoT through real-time monitoring, reviewing and providing apt solutions by itself.
- Fault Tolerant: By inculcating with Distributed databases, it can create a fault resistant system where if one of the components goes offline or is malfunctioning, it won’t affect the entire system.
- Scalability: Modern operational database systems are ever ready to scale on request and with the added advantage of high concurrency and low latency. Businesses can adopt the “Use as you grow “principle.
- Big Data: Operational Database with distributed systems and NoSQL based system can harness the true potential with big data using technologies like Hadoop along with operational DBMS like Cassandra or MongoDB
Functions of an Operational Database
Functions of an operational database are given:
1. Indexing and Cataloguing
The main function of a Database system is Indexing which refers to efficiently store data that can be retrieved when requested with ease. It is divided into Primary, Secondary and clustered Indexes. Cataloguing refers to assigning key attributes to a file and can be then used to recall effectively like a book or a journal.
Put simply, it refers to making a copy of file or data as a whole at multiple locations so as to ease the retrieval and storage process. This is particularly important in distributed systems where the same data when stored at multiple locations can be accessed more easily and with added consistency.
3. File Storage, Structure
File storage is another important function of the operational DMS where since its use cases are complex so does the system of storing the files. The system needs to be robust enough to sort and store files at relevant locations. The file organization system can organize files in Heap, Sequential, Hash, Clustered file organization system.
4. Query Processing
Operational database systems get the analytical ability due to its superior query processing system. It refers to the entire process from translating a query put forward to the database system by users into simple low-level instruction to its optimization and analyzing and evaluating the query. After the process, the system would extract relevant data from the database and present it to the user. This process happens in a fraction of a second.
5. Transactions Support
A transaction system can be considered the logical unit of the operational database system. For it working consistently in a steady-state, in a concurrent state and having recovery services is of paramount importance. Transaction support deal with this along with making the system ACID-compliant which means Atomicity which distinguishes a transaction from others, Consistency which ensures that the transaction changes database during the process doesn’t make it inconsistent, Isolation which refers to keeping the transactions independent in a concurrent state and Finally Durability ensuring the transaction are permanently stored in the dataset along with the end result of processing.
Following are the advantages given below:
- Operational Databases systems are greatly versatile and accommodate distributed systems like NoSQL, SQL, New SQL Databases.
- These systems are highly available, fault-tolerant and highly scalable as discussed.
- They are highly secured as they offer built-in support for encryption, auditing, and protection from cyber
- They are extremely flexible and can work with multiple applications without losing the state of the database. Therefore, people at different locations or a department can incorporate application and services as per their needs without worrying about the state of the database.
- Such systems are often more economical as systems in an operational database are usually based on distributed networks and systems thereby reducing costs drastically and ensuring consistency.
Following are the disadvantages given below:
- They usually have a learning curve where personnel are required to give relevant training to manage such databases and that increases the overheads expenses
- Even the installation process of such an operational database system requires time and effort where they need to be set up in an optimal way of meeting business goals and extracting most benefit from the system.
- Security could also be an issue where since the data is stored in a remote location having overall control could be difficult and we have seen recent examples of customer data being hacked from some of the most prominent tech companies.
As discussed, in spite of some disadvantages there is no denying that an operational database is the most effective and efficient way of managing all data in an organization. Most Fortune 500 companies use applications that use this method of database management.
Therefore, it is important for anyone to understand operational databases and its architecture who wants to make a career in Data Science and Big Data along with working knowledge of other technologies like Hadoop, Cassandra, and MongoDB.
This is a guide to an Operational Database. Here we discuss the Introduction, need, functions of an operational database along with advantages and disadvantages. You may also look at the following articles to learn more –
- Data Lake vs Data Warehouse | Key Differences
- Data Warehouse Testing
- Types of Test Case
- Test data generation tool