What is Data Persistence?

Data persistence: An introduction

An application creates data. And, at some point, the user quits the application. But what happens to the data? This is where data persistence comes into play.

Data persistence refers to the capability of an application to save data so that it can be retrieved and used later, even after the application has closed or the system has been restarted. It ensures that the data remains intact and accessible across different sessions of an application.

This introductory article will provide a basic introduction to help you get started and understand the basic vocabulary used in regard to data persistence.

We'll explore the mechanisms behind data persistence, the types of storage used, and why it is essential for both personal and business applications. By understanding data persistence, you'll be better equipped to manage and protect the valuable information generated by your applications, ensuring a seamless user experience and consistent data integrity.

Table of contents

• Persist data at the user level vs. application level
• Data persistence and applications
• Why is persistence important in programming?
• Persistent vs non-persistent data
• How do you ensure data persistence?
• Can data persistence be achieved using a database system?
• Final thoughts on using data persistence in databases
• FAQs

What is data persistence?

Data persistence is the longevity of data after the application that created it has been closed. In order for this to happen, the data must be written to non-volatile storage — a type of memory that can retain that information long-term, even if the application is no longer running.

Non-volatile storage can be anything from a traditional hard disk drive (HDD) to cloud storage solutions.

Importance of data persistence

When data is persisted, it means that the exact same data can be retrieved by an application when it's opened again. The data remains consistent, and nothing is lost between sessions. This is crucial for maintaining data integrity and ensuring that users have a seamless experience across sessions.

Local storage versus remote storage

There are different ways to persist data, which brings us to an important distinction: local storage versus remote storage.

Think of a Word document that you open to write an article like this one. When you're done writing for the day, you click on Save, choose a location on your computer, and you're done. The data — in this case, your Word document — gets saved on your disk and can be accessed the next time you start Word again.

The role of remote storage

Now, what if you wanted to edit this Word document on your laptop rather than on your desktop? Therein lies the difference between local and remote storage because remote persisted storage would allow this.

Let's say the location you saved your Word document in is actually not just any folder but your Google Drive folder on your disk. The Google Drive application will then automatically send this file to your Google Drive cloud to save it remotely and securely.

Long story short, data persistence is the difference between data getting lost between sessions and data remaining consistent between sessions.

Persist data at the user level vs. application level

The Word document we mentioned earlier is an example of data persisted at the user level. User-level data persistence means that the data is saved in a manner where only the specific user who created or owns the data has access to it. This type of persistence is essential for maintaining privacy and personal control over data.

For example, personal documents, user settings, and preferences saved on your device are all examples of user-level data persistence.

Only you, the owner of these files, can access and modify them unless you explicitly share them with others.

User-level data persistence

User-level data persistence is crucial for personal productivity tools, ensuring that sensitive information remains private and secure.

When you save a Word document on your laptop, it is stored in a folder specific to your user profile, ensuring it is available only to you.

Application-level data persistence

On the other hand, application-level data persistence refers to data that is saved and accessible to all users of the application. An excellent example is a comment below a YouTube video.

When you post a comment, it gets stored in a central database managed by YouTube, and anyone who watches that video can see your comment. Comments are saved at the application level, making them readily accessible to all users, ensuring a shared experience.

Examples of application-level data persistence

Application-level data persistence is common in social media platforms, collaborative tools, and content management systems. In a social media app like Facebook, posts, likes, and comments are stored at the application level, allowing all users to interact with shared content seamlessly.

In collaborative tools like Google Docs, multiple users can access and edit the same document simultaneously, with changes saved in real-time at the application level.

Understanding the distinction between user-level and application-level data persistence helps in designing systems that balance privacy, security, and accessibility, ensuring both individual privacy and collective collaboration.

Data persistence and applications

Apart from keeping your data safe, you might wonder why data persistence is important in your application.

Imagine using an app that asks for your name and email address the first time you start it. If you close the application and have to re-enter your data upon reopening, the user experience suffers. Persisting user-provided data ensures that it remains consistent and readily accessible, improving the user experience (UX).

Performance is key

Performance is another key factor. Consider an email app on your phone. Without local storage persistence, you would need to download every email each time you open the app. Persisting emails locally saves disk space and reduces network bandwidth usage.

There are many solutions for data persistence, depending on your use case.

From relational databases to object-based databases and document databases like MongoDB, the world of data persistence is vast and versatile.

Why is persistence important in programming?

Persistence in programming is crucial because it allows data to be stored and accessed consistently across various applications, devices, and operating systems. For instance, consider accessing your data through different interfaces, such as a web browser on your laptop and a mobile app on your smartphone. Both of these access points are built differently but rely on the same underlying data, thanks to persistence.

When data is persisted, it ensures that no matter where or how you access it, the information remains consistent and up-to-date. This cross-platform accessibility is essential for maintaining the integrity and usability of data in a world where users interact with their data through multiple devices and applications.

Client-side benefits of data persistence

Let's talk again more specifically about the client-side benefits. From a UX perspective, data persistence means that you don't have to ask the user for the same information more than once.

In terms of performance, the app doesn't need to download the same data over and over again. Server-side persistence is also beneficial. For example, Google Drive saves everything in the cloud and only downloads it when needed. This saves disk space on the client side.

Persistent vs non-persistent data

Persistent data always maintains the last version (or even multiple versions) of itself even after it’s been modified. If data is persistent, then it’s sustained even if the process, cluster, node, or container is changed or removed.

If data is non-persistent, this means that it can be altered, removed, or lost if the process, cluster, node, or container is changed or removed.

How do you ensure data persistence?

There are various ways you can make sure that data persists. One of the more common methods is to take periodic snapshots of your disk at a configurable interval. Here are a few other approaches:

• Saving data in a file
• Saving your data to a local device database like Atlas Device SDKs
• Sending data to a server
• Saving data to external storage, like a USB stick
• Saving your data in a remote database like MongoDB Atlas
• Printing out your data

Can data persistence be achieved using a database system?

Yes! Databases are one of the most common and effective ways of achieving data persistence. Data persistence ensures that data remains consistent and accessible even after the application that created it has closed. This is crucial for maintaining data integrity and providing a seamless user experience.

Whether you're using a document database like MongoDB, a relational database system, or other types of databases, data persistence can be effectively managed and maintained.

Key benefits: Databases and data persistence

• Consistent data access: Databases ensure that data remains consistent and can be accessed across different applications, devices, and operating systems. This is crucial for providing a seamless user experience and maintaining data integrity.

• Storage solutions: Databases offer various storage solutions, from local storage to cloud storage, allowing for flexibility in how data is stored and managed. For example, MongoDB Atlas provides a fully managed cloud database service, ensuring data is stored securely and is readily accessible.

• Data management: Databases provide robust data management capabilities, including backup and recovery, indexing, and data replication, ensuring that data is safe, secure, and available when needed.

Final thoughts on using data persistence in databases

Achieving data persistence using a database system is essential for ensuring that data remains consistent, accessible, and secure across different applications and devices.

Whether using document-based databases like MongoDB or relational databases, leveraging the capabilities of these systems can significantly enhance data management and user experience. By understanding and implementing data persistence strategies, organizations can ensure that their data remains intact and readily available, supporting robust application development and reliable data storage.