Do businesses really need real-time analytics? Data startups are counting on it.

The term "real time" has been infused throughout tech, from real-time stock picks to real-time pizza tracking. As everyday enterprises begin incorporating data tools and tactics used inside the biggest of big tech companies, a sector of data services providers has emerged to help them take advantage of the truly real-time analytics and machine learning approaches only giant companies with far larger database teams and resources could have afforded in the past. Companies like Hazelcast, Rockset, Tecton and others enable split-second analytics and machine learning for things like financial fraud prevention, dynamic pricing or product recommendations that respond to what you just clicked. These companies promise to leave plodding batch-data processing for old-school business intelligence analysis in the dust. But whether every enterprise needs, wants or is ready to operate at a clip as fast paced as a Citibank, Uber or Amazon remains to be seen. Updating data every few days, every night or even every hour or so for business analysis using a typical batch processing approach "is like playing Monday morning quarterback," said Venkat Venkataramani, CEO and co-founder of Rockset, a company that provides a database for building applications for real-time data, analytics and queries.