Raj Verma is the CEO of single store. He brings over 25 years of global enterprise software and scaling experience.
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Large database players MongoDB and Snowflake recently updated their tech stacks to support trades and analytics. As the CEO of another database company, I think these developments help highlight the market’s shift to modern cloud-native technology that provides streaming, operational, and analytical processing in a single database.
It is important that modern database architectures can handle the speed and variety of data we encounter in today’s digital service economy. Most importantly, I think they should be equipped to handle real-time changes all in one place, without moving data around.
But what is real-time, why is it important for a database and what do the above developments mean for the future of data and real-time possibilities?
Why are real-time analytics important?
Many companies are now service providers in today’s digital services economy. In this environment, businesses need real-time applications to survive and thrive. As the digital economy grows, 72% of consumers say poor personalization reduces their trust in brands, according to Adobe’s 2022 Trust Report.
Many of the services and applications people use today – from ride-hailing services to the real-time tracking services offered by several major pizza brands – use real-time analytics to provide action and responses in milliseconds (as opposed to minutes, hours, or days) . Real time is critical as customers stop waiting for you and move on.
Real-time analytics can enable a company to make informed, fast decisions. For example if Protocol recently reported, real-time databases could “enable split-second analytics and machine learning for things like financial fraud prevention, dynamic pricing, or product recommendations.”
What are real-time requirements?
Realtime starts with the storage architecture, that’s what makes things fast. Where you store data and the forms you store it in determine how quickly you can retrieve the data. This requires a modern database that leverages technology and processes that enable transactional and analytic workloads to keep businesses current with the ability to drive innovation and gain competitive advantage. Real-time means that data does not move back and forth. Instead, there is a central place for transactional and analytical data. This is how companies can become lightning fast.
Real-time decisions are made at data birth, which is often based on semi-structured data such as JSON. This type of analysis cannot wait for a conversion to Parquet or CSV to take place. Rapid ingestion and analysis of semi-structured data is important for real-time scenarios.
Some existing database players have recently made real-time announcements and new players have emerged in this arena. This was a positive development as it again highlighted the importance of having transactional and analytical support in a single database. It is clear to me that combining transactional and analytical support is the right approach.
How can companies get started with real-time data?
First, consider the poor data experiences your existing infrastructure might provide. Ask yourself what your current processes are and what they mean for you and your customers: Are my operational dashboards running too slowly? Is my trip calling app not displaying accurate prices? Did my organization miss a fraudulent payment?
Once you’ve identified such issues, get to work on addressing them. Start by assessing the data intensity of your existing applications. Consider the rate at which your data-intensive applications are likely to grow over the next year and beyond. To do that, it’s important to measure the concurrency of your data, the ingestion rate and size, and the complexity, concurrency, and latency of your queries. Then you better know where you are, where you are going and what infrastructure your applications need and will need in the future.
This assessment will better position you to identify and implement the right data infrastructure. With the right data infrastructure, you can leverage available data and real-time analytics to deliver the experiences customers, employees, and partners want and expect.
Embrace simplicity.
To improve your data infrastructure, I also recommend that you stop piling on specialized databases to meet each new application requirement. This only adds complexity and cost. Instead, embrace simplicity.
Also avoid moving data. I’ve noticed that the more data is moved, the slower it gets. Moving data can also increase costs, slow down your ability to introduce new features and services, and negatively impact application performance. Instead, centralize all your data. And make sure you centralize both your transactional data and your analytical data.
Understand that you don’t need to switch to a single database all at once. Select the projects by importance or pain points to start your journey with this new solution. The available technology makes it possible to gradually accelerate or expand your data infrastructure. You can expand from there to more effectively use real-time data and analytics to drive results across a wide range of industries and use cases such as security threat detection and analysis, stock trading strategies based on market events, credit card fraud detection, sensor data analysis to detect maintenance requirements, behavioral analysis on gaming and other online click traffic and more.
Stand out from the competition.
I believe the future of the database industry lies in a modern, all-in-one database that enables organizations to avoid aggravated performance, latency, and quality issues and ensure data integrity, quality, and reliability. This is critical today and tomorrow as companies are able to gain insights and react in real time to differentiate themselves from their competitors and delight their customers.
Even with economic uncertainty, I believe the database industry will hold up. In this climate, companies can lag if their data architecture doesn’t provide real-time capabilities.
I predict we’ll continue to see more databases that offer real-time analytics. But I think it will be the unified databases that contain four main features – distributed, shared nothing architecture, cloud native, a multi-model and relational basis – that will prevail. It’s going to be very interesting.
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