To ensure that users always have access to their information, computers use storage resources to keep data persistent and available even after they’re powered down. Persistent data does not disappear when a computer loses power. Users can retrieve their files and data even after a power outage using persistent storage such as a local storage device or network storage.
What Is Persistent Data?
Persistent data is any data stored on a non-volatile storage medium that remains accessible for long-term use until it’s purposefully deleted or overwritten. Persistent data will remain even after the device’s power is turned off.
Computers have primary storage in the form of random access memory (RAM). RAM is fast and stores gigabytes of data for applications to retrieve and for the central processing unit (CPU) to perform calculations. When the computer is powered off, RAM can no longer store any data. RAM in a computer needs consistent power refreshes, so non-persistent data stored in primary storage is lost when a computer is powered off.
To ensure users can return to their data after a power outage, computers use secondary storage disks to keep data persistent and available. Persistent data includes the files and applications stored on a secondary storage device that continues to be available even after a power outage. The secondary storage device that keeps data persistent could be an internal disk, an external flash drive, or an array of storage devices on a network (e.g., network attached storage).
How Does Persistent Data Work?
Most computers have one of two types of drives to store persistent data: a solid-state drive (SSD) or a hard-disk drive (HDD). Some computers have a hybrid storage system with both an SSD and an HDD. An SSD is a type of flash storage that stores data even after the computer is powered off. An HDD is a series of spinning platters that persist data using magnetism. Both drives are viable options for persistent data, but an SSD is often preferred for application performance. HDDs are preferred for backups and recovery.
Cloud storage also offers businesses resources for persistent data. Companies can choose to store all of their data in the cloud, or they can use a hybrid model and store only some of their data in the cloud. The advantage of the cloud for persistent data is that it’s more secure, available, and requires less maintenance from staff.
Examples of Persistent Data
Persistent data comes in several forms. For example, a database stores data to disk drives to retrieve it for application and user queries. Both relational databases and NoSQL databases use persistent data for backend processing and querying. The analytics applications used to drive marketing and sales might use a NoSQL database and machine learning for future predictions. A basic e-commerce store might use a relational database to store product information and customer orders.
Every saved file stored on a disk is a form of persistent data. When users store a file on their local disk or in the cloud, the files are stored on a disk where they can be accessed and retrieved in the future. Most cloud storage has backup and security baked into features, so any hardware failures do not destroy data permanently.
Unstructured data is known as object storage, and it persists using NoSQL databases. Businesses can store documents and collect data with no specific format or structure and store it in data warehouses with NoSQL databases used to query and retrieve it. Object storage requires large amounts of disk space, so it’s often offloaded to cloud resources to save money and leverage scalability options.
Persistent Data vs. Volatile Data
Primary storage holds volatile data. Volatile data does not persist after a power outage, so computers need a secondary disk to keep data viable after power is turned off. Computers use dynamic RAM (DRAM) and static RAM (SRAM) for storing volatile data and cached information. DRAM and SRAM are faster than persistent storage, but their volatility requires a secondary storage device.
Cloud providers often offer in-memory databases as a way to offer application fast performance for queries and real-time data delivery. In-memory databases use volatile memory to store application data, which makes them fast but creates the risk of lost data after a hardware failure. A combination of in-memory processing with persistent data storage is the best solution for most business applications.
An example use case for in-memory databases is real-time bidding. Users bid on a specific product and another user might bid within milliseconds. These bids must be available nearly instantaneously for other bidders to get accurate information. The bidding system uses in-memory databases to keep bid amounts updated, but bid information is still stored on persistent data storage disks.
Persistent Data vs. Dynamic Data
Most data must be changed often or infrequently. For example, your social security number might possibly change in your lifetime, but your home address will probably change more often. Dynamic data is data that updates or changes occasionally, and businesses need a way to update their stored data as needed. Most standard databases allow businesses and their applications to update dynamic data.
Businesses can purchase dynamic data to ensure that they have the most up-to-date information for services and customer support. For example, a real estate company needs continually updated data to monitor new homes on the market and changes to housing prices. Importing dynamic data from a third party keeps a real estate company’s stored data current so that they can offer customers effective services.
Persistent data is a form of dynamic data, but it could also be static data. Static data does not change, but it persists on a storage device. Dynamic data also persists on a disk, but applications and users can change data as often as they want. Changes to dynamic data are also stored to disk so that updated information is available to users.
Benefits and Drawbacks of Persistent Data
Every business needs persistent data, but the challenge is to preserve data integrity and availability after changes are made to it. Most databases have advanced technology to reduce “dirty reads” causing incorrect data to be returned and potentially stored to disk. Log files keep track of database transactions to avoid loss of data integrity.
Businesses must have a plan for data storage to keep data consistent and secure. Data should be normalized so that data remains consistent across all applications and does not update in multiple places leading to possible inaccuracies. All data should be secure using authentication and authorization rules, and monitoring systems should be in place to detect any suspicious activity.
Cloud storage offers a flexible option for businesses to keep IT budgets low while reducing maintenance overhead. Administrators have built-in features for securing database backups and production data, and they do not need to maintain hardware. Businesses should always have backups of their persistent data, and the cloud offers the scalability to increase capacity as more data is collected and stored.
Conclusion
For every business, both primary and secondary storage are necessary. Secondary storage keeps data available even after a power outage. Since data is not lost on a disk, it’s considered persistent data. Persistent data is a critical component in business productivity, and the most flexible and scalable option is cloud storage. Looking for the best persistent storage solution for container workloads? Check out Portworx® today.
