In the age of manual decision making based on predictable data formats, data feeds, and batch processing times, enterprise businesses stayed current with ad hoc analyses and periodic reports. To generate analyses and reports, businesses relied on the traditional data warehouse. Using extraction, transformation, and load batch processes, the traditional data warehouse standardized disparate data into normalized schemas and pre-computed cubes. With the data shaped into pre-configured dimensions and aggregated facts, enterprises made historical data and analyses available to front-line decision makers.

In today’s age of digital business, machine learning, and artificial intelligence, decision making for companies is now very different. It is based on unpredictable data formats, massive data scale, event messaging, stream processing, models training, historical analyses, predicitve analytics, and real-time dashboards.

The Enterprise Shift to Real-Time

Today’s real-time economy is segmented, scored, personalized, appified, monetized, and data fueled. Aligning today’s enterprise business with the on-demand, digital economy requires real-time data storage and analytics.

“Companies like Pinterest, Uber, and Pandora have achieved significant performance advantages by shifting from a batch process to a continual load of data.”
– 
Eric Frenkiel, MemSQL co-founder and CEO

The real-time data warehouse embraces perpetual data ingest, simultaneous reads, high user concurrency, and fast queries. This new data warehouse continually loads and transforms data, one transaction per event or message with exactly-once semantics.  The real-time data warehouse is the foundation for today’s enterprise business that is synchronized with the market and its profit-making opportunities.

The Real-Time Enterprise Gets Its Data Warehouse

In a MemSQL data warehouse, where there is continual data ingest at massive scale, disparate business data is made whole for the various applications running on top of the data warehouse.

“For many enterprises today, moving to real time is the next logical step, and for some others it’s the only option.”
– 
Nikita Shamgunov, MemSQL co-founder and CTO.

Data analysts run real-time ad-hoc analyses in sub-seconds.  Data scientists train and evaluate machine learning models within minutes. Apps predicatively score and deliver personalized experiences. Armed with a customer 360 degree view of critical business metrics, front-line decision makers automate actions that drive value.

Where Real-Time Data Warehousing Matters

In today’s market, enterprises need the flexibility to migrate, expand, and burst their storage and compute capacity both on-premises and in the cloud.

“MemSQL is the most flexible data warehouse in the market today.”
– 
Eric Frenkiel, MemSQL co-founder and CEO

With MemSQL, businesses push real-time workloads where it is the most economical to run them. For companies succeeding in the real-time economy, MemSQL is the hybrid cloud data warehouse that offers these critical operations and cost-savings advantages.

Learn more about how and where real-time data warehousing matters from MemSQL co-founders, Eric Frenkiel (CEO) and Nikita Shamgunov (CTO), in this insightful video.



Business Intelligence, Data Driven Decision Making, Real-Time Data Processing