REAL Real-time Data Analytics: When Seconds Matter By Teresa Wingfield April 7, 2023 According to Gartner, real-time analytics is the discipline that applies logic and mathematics to data to provide insights for making better decisions quickly. For some use cases, real-time means analytics is completed within a few seconds after the arrival of new data. Actian calls this REAL real-time data analytics. Analytics solutions vary greatly in their real-time capabilities, with many having only “near” real-time analytics. REAL real-time analytics means that you can immediately deliver real-time data and consistently execute ultra-fast queries to inform decisions in the moment. Here’s a quick overview of how the Avalanche Cloud Data Platform achieves these two requirements. Real-time Data Real-time data is information that is delivered immediately after collection. This requires real-time, event and embedded processing options so that you can ingest your data quickly. You will also need integration that includes orchestration, scheduling, and data pipeline management functionality to help ensure that there is no delay in the timeliness of information. The Avalanche Cloud Data Platform is noted for its fast delivery of real-time data using the above data integration features. In a recent Enterprise Strategy Group economic validation, customers reported that the Avalanche platform reduced data load times up to 99% and reduced integration and conversion time up to 95%. Real-time Queries A columnar database with vectorized data processing has become the de facto standard to accelerate analytical queries. While row-oriented storage and execution are designed to optimize performance for online transaction processing queries, they provide sub-optimal performance for analytical queries. A columnar database stores data in columns instead of rows. The purpose of a columnar database is to efficiently write and read data to and from hard disk storage to speed up the time it takes to return query results. Vectorization enables highly optimized query processing of columnar data. Vectorization is the process of converting an algorithm from operating on a single value at a time to operating on a set of values (vector) at one time. Modern CPUs support this with Single instruction, multiple data (SIMD) parallel processing. Additional optimizations such as multi-core parallelism, query execution in CPU cores/cache, and more contribute to making the Avalanche Cloud Data Platform the world’s fastest analytics platform. The Avalanche platform is up to 7.9 x faster than alternatives, according to the Enterprise Strategy Group. The Avalanche platform also has patented technology that allows you to continuously keep your analytics dataset up-to-date, without affecting downstream query performance. This is ideal for delivering faster analytic outcomes. When Seconds Matter So why does speed matter? Real-time data analytics allows businesses to act without delay so that they can seize opportunities or prevent problems before they happen. Here is a brief example of each type of benefit. Online Insurance Quotes Insurance comparison websites in the UK give top billing to insurers who respond fastest to online requests for quotes. Insurance uses the Avalanche platform for real-time analytics to deliver a risk-balanced, competitive insurance quote with sub-second speed. Proactive Equipment Maintenance As manufacturers incorporate more IoT devices on their plant floors, they have opportunities to analyze data from them in real-time to identify and resolve potential problems with production-line equipment, before they happen, and to spot bottlenecks and quality assurance issues faster. The Actian Data Platform a single solution for data integration, data management, and real-time data analytics. Check out how the platform lets you integrate anytime. About Teresa Wingfield Teresa Wingfield is Director of Product Marketing at Actian where she is responsible for communicating the unique value that the Avalanche Cloud Data Platform delivers, including proven data integration, data management and data analytics. She enjoys applying her extensive knowledge in these areas to help customers find solutions that will help them achieve long-lasting success. Teresa brings a 20-year track record of increasing revenue and awareness for analytics, security, and cloud solutions. Prior to Actian, Teresa managed product marketing at industry-leading companies such as Cisco, McAfee, and VMware. She was also Datameer’s first VP of Marketing for big data analytics built on Hadoop, and has served as VP of Research at Giga Information Group, acquired by Forrester, providing strategic advisory services for data warehousing and analytics. Teresa holds graduate degrees in management from the MIT Sloan School of Management and software engineering from Harvard University.