Comparing Real-Time Databases

While traditional databases contain permanent data that changes infrequently, real-time databases handle data workloads that are continually changing and time sensitive. A real-time database also uses real-time processing to manage its data, meaning that transactions — or units of work performed within the database — are processed quickly enough for organizations or other integrated systems to instantly utilize the data.

Real-time databases are vital tools for many sectors, including eCommerce, energy, fintech, healthcare, high tech, retail, utilities and transportation. For example, an air traffic control system constantly analyzes large numbers of aircraft, keeps track of current values, makes choices regarding incoming flight patterns and calculates the sequence in which aircraft should land based on variables like weather, fuel, altitude and speed. If any of this data takes longer than expected to process, the consequences can be severe.

In this article, you will learn about real-time databases and their use cases. You’ll also explore different types of real-time databases and the features they provide, including low-latency streaming data, flexible indexing and high availability — so you can see what advantages they offer for various businesses.

About Real-Time Databases

A real-time database is similar to a conventional database, but its data validity is strongly dependent on time; if the execution deadline is missed, data becomes obsolete. Due to its timeliness requirement, one or more atomicity, consistency, isolation and durability (ACID) properties are sometimes relaxed to process transactions promptly while providing better support for temporal consistency.

Real-time databases are the fastest option for real-time analytics, meaning they facilitate data-driven decisions. They allow software administrators to evaluate which data sets are relevant to a specific geographic region by receiving the appropriate response and updates in real time. They also enable seamless spotting of statistical anomalies caused by security breaches, network outages or machine failures. And businesses’ stakeholders can evaluate the data acquired from customer behavior, inventories, web visits and demographics in real time for insights to improve usability, audience targeting, pricing strategies and conversion rates.

As we’ll lay out, there are two types of real-time databases: hard and soft. These classifications are determined by the transaction deadline. Additionally, a research paper by Ben Kao and Hector Garcia-Molina states that a transaction that misses its deadline is called a “tardy transaction.”

Hard Real-Time Databases

A hard real-time database is a system with hard deadline transactions, meaning that timely and logically correct execution is critical. Missing hard deadlines could lead to serious consequences, including incorrect patient data or significant financial loss, depending on the use case. Hard deadlines are sometimes referred to as safety-critical deadlines.

Hard real-time databases

The preceding graph is a representation of hard deadline transactions that require a prompt response to be efficient. The data drops in value (actual effectiveness) immediately after a deadline is missed.

If a transaction misses its deadline in a hard real-time database system, the system neglects the tardy transaction (that is, it doesn’t attempt to execute that transaction again) so that other transactions may have a better chance of meeting their deadlines. This is why hard real-time databases are only used in safety-critical systems, where the system cannot afford to have a tardy transaction.

Some of these safety-critical systems include emergency alarm systems, antimissile systems, patient monitoring systems and air traffic control systems.

Soft Real-Time Databases

A soft real-time database has soft deadline transactions, and missing a deadline does not result in a failure or a breakdown of the system’s integrity. However, the quality of the results declines after the deadline, potentially affecting the database system’s quality of service.

Soft real-time databases

The preceding graph represents soft deadline transactions, in which the value (actual effectiveness) decreases over time.

When a tardy transaction occurs in a soft real-time database system, the system will try to execute it again, but it will lower the priority so that non-tardy transactions are executed first. However, the system will neglect the transaction if the actual effectiveness has decreased to a negative value.

Soft real-time databases are used in banking systems, reservation systems, digital library systems and stock market systems.

Real-Time Database Use Cases

Organizations in various sectors adopt real-time databases to respond to events quickly and analyze data as it is generated. The following are some example use cases in industries including energy and utilities, gaming and media, and retail and eCommerce.

Energy and Utilities

In the energy and utility industry, generation, transmission and distribution facilities are all sources of critical data needed to optimize technical and business operations. This critical data is dynamic due to various factors like energy consumption, severe weather conditions and gas availability. As a result, this dynamic data must be managed in real time to avoid energy and financial loss and facility hazards.

Businesses in this industry are encouraged to adopt real-time databases because they will be able to perform real-time analysis of the dynamic data collected from these sources and use that analysis to optimize plant operations promptly, regulate energy usage and detect maintenance issues and equipment damages at an early stage.

Here’s how a major oil and gas company utilized SingleStore to improve its financial operations.

Gaming and Media

Real-time databases allow gaming and media companies to analyze usage patterns and behavior from online games, streaming videos or social media applications. This allows companies to improve user experience by providing more personalized recommendations tailored to each user’s preferences. Software administrators can also seamlessly monitor service quality.

Real-time databases also facilitate collaboration in the gaming and media industries. In other words, different people can control the same entity in an online game or work on the same document (including on text, images or video) simultaneously.

Retail and eCommerce

Real-time databases enable eCommerce systems and apps to handle consumer requests within their deadlines — like when market status changes — by using updated data indicating the current market status.

Additionally, real-time databases enable retail and eCommerce platforms to analyze user patterns and behavior, using the insights to present personalized and recommended products and detect fraud in real time.

Characteristics of Real-Time Databases

Among the features that real-time databases offer are performance, queuing, flexible indexing and high availability in case of hardware failure and historical records.

Performance

One of the most significant characteristics of a real-time database is the ability to process and complete transactions within deadlines. Regardless of whether there are hundreds or tens of thousands of events per minute, the database should be able to process everything without missing any deadlines — and respond to the system with minimal or no delay.

Queuing

The real-time database should be able to manage a massive number of events in the proper sequence — that is, its queuing model should keep the order of event inputs in the backlog and execute them in that order.

Flexible Indexing

Real-time databases, like SingleStoreDB, come with a number of indexing options to meet your development use case and enable low latency or minimal delay to data access in a variety of circumstances. Some of these indexes include the shard key, which is responsible for partition data distribution; the columnstore sort key, which stores data on disk in a columnstore format; and the skiplist index, which is a data structure suited for ordered data that allows queries to quickly seek data by binary searching.

High Availability in Case of Hardware Failure

High availability is the ability to remain available during a hardware failure without any service disruption. Its goal is to provide long-term, uninterrupted access to an application, and it usually involves the use of at least two servers, each running on different hardware. It can use redundant hardware on each server if desired and operate servers inside virtual machines that automatically switch from failing to working hardware.

This feature requires techniques to identify hardware failure as well as processes to ensure that a failing server remains offline so that data is not processed incorrectly and inconsistencies are avoided. It also includes the ability to automatically switch databases and notify connected applications to reconnect to the running database server.

Historical Records

Keeping track of historical data allows you to spot developing trends as they emerge so that you can make the required adjustments to preserve your system’s performance, availability, and security. Real-time databases should be able to record and store data in a timely manner, allowing for easy future access. Keeping your log data for as long as possible not only aids in resolving issues (since you can gain insights from log files from several months or years ago) but also allows you to extract more present-day value from the data.

For example, say you are investigating the root cause of an air mishap that happened over five years ago. You will be able to analyze the data that was logged during that air mishap to improve the functionality of the air traffic control systems and other systems related to the incident.

Conclusion

Real-time databases enable organizations to quickly and efficiently analyze current and historical data so that they can respond quickly to trends or resolve problems. As you learned in this article, these databases can improve the usability, engineering, and market performance of applications in multiple sectors.

If you’re in search of a real-time database to manage your applications, consider SingleStoreDB. SingleStoreDB specializes in real-time operational analytics and supports cloud-native SaaS applications. It provides global organizations with a distributed SQL database that unifies transactions and analytics.

SingleStore is well suited for delivering analytics in real time and is utilized by some of the world’s largest and most demanding businesses, including Uber, Comcast and Hulu.

Try SingleStoreDB free.

Comparing Real-Time Databases