From finding a new show based on a recommendation from your streaming service, to getting fraud alerts from your bank, you benefit from both real-time applications and analytics every day.
Behind the scenes, these daily touchpoints online and in the marketplace require a powerful database architecture to work as they should — one that is designed to keep up with fluctuations in users, scalability and demand.
Let’s be honest: most consumers aren’t concerned with how their experience is powered, so long as apps are available and functioning in real time. If an application takes too long to load, or provides recommendations that don’t fit with your taste, you’re likely to turn elsewhere.
But what about when you’re the one providing the application or service? How can you meet real-time experiences today’s users don’t just want, but expect? It starts with your database architecture.
Our eBook, “3 Key Attributes of a Modern Application That’s Ready for Real Time” dives into the key features your database architecture needs to make the most of live data — ensuring your application stays competitive.
Feature #1: Ultra-Fast Ingest
As your business — and user base — grows, so does your data. It’s critical your database architecture keeps up, continuously ingesting data from diverse sources as it’s generated while also making sure that data is available for indexing and querying.
The answer? SingleStoreDB Pipelines. Pipelines allow users to continuously extract, optionally transform and load data in parallel at ultra-fast speeds — as in, 100-billion-rows kind of fast.
Think your application could use that kind of power?
Feature #2: High Concurrency With Low Latency
At normal times, your application might handle thousands of users. At peak times, this number can drastically increase into the hundreds of thousands. And if your database architecture can’t handle this high concurrency, your application won’t be available — and you’ve lost customers.
What you need is a database that delivers low-latency performance when high volumes of users are accessing your application at the same time. SingleStoreDB supports customer-facing applications with 40,000+ users through seekable columnstores. Simply put, SingleStoreDB incorporates hash indexes on columnstores, resulting in less information to sift through so the database can answer queries quickly — and has more capacity to handle multiple users.
See more: How GE Solved 100+ Use Cases and Reduced Auditing Costs by 40x With Self-Serve, Real-Time Data From SingleStoreDB
Feature #3: Artificial Intelligence (AI) and Machine Learning (ML) Capabilities
If you haven’t started incorporating AI and ML into your data architecture, you might be behind the curve. AI and ML can lower costs, increase scale, speed up the delivery of results and achieve critical business goals. Together, these capabilities deliver real-time analytics, predictive analytics and more.
But AI and ML can be difficult to incorporate without the right data infrastructure in place — which requires a high-performance platform to complete calculations within the model (usually across a mix of streaming and historical data). SingleStoreDB delivers maximum performance for both transactional (OLTP) and analytical (OLAP) workloads, using familiar relational data structures.
Additionally, the SQL compatibility of SingleStoreDB makes it an ideal choice as a platform for developers operationalizing ML models as part of user-facing, real-time applications.
Ready for Real-Time Applications?
To read more about what your database architecture needs to support truly real-time applications, download your copy of the eBook,“3 Key Attributes of a Modern Application That’s Ready for Real Time”today.
Check out these additional resources for real-time applications: