There are many different methods to persist data with some examples being a database or in memory storage. The goal of this project aims to separate the application logic data from the storage mechanisms
Persisted data, often referred to as persistent data, is information that is stored and retained beyond the current session or execution of a computer program or application. In the context of software development and data management, “persistence” refers to the ability of data to survive even after the program that created or manipulated it has terminated or the system has been shut down. This allows the data to be accessed, retrieved, and used again in future sessions or instances of the program.
File-Based Persistence: Data can be saved in files on the file system, such as text files, JSON files, XML files, or binary files. These files can be read and written by the program, enabling the data to be stored and retrieved between different program runs.
Database Persistence: Databases are specialized systems designed for storing and managing large amounts of structured data. Persistent data can be stored in databases using relational database management systems (RDBMS) like MySQL, PostgreSQL, or in NoSQL databases like MongoDB. This form of persistence offers more advanced querying and data manipulation capabilities.
Memory-Based Persistence: While not as permanent as file or database persistence, some data can be kept in memory across program executions. This is often used for caching frequently accessed data to improve performance, but this data is typically not as durable as other forms of persistence.
Cloud-Based Persistence: Data can be stored on remote servers or in cloud-based services, providing access from various locations and devices. Cloud storage services like Amazon S3, Google Cloud Storage, and Microsoft Azure Storage offer persistent data storage options.
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