Data is like music, made up of different components, with the spaces, gaps, and rhythm critical to understanding and appreciating the whole. Just as with music, data can be analyzed and enjoyed in real time (stream analytics software) or as a past, documented record (log analysis software).
Confluent’s big funding round showcases the rise of stream analytics
Although the former is a newer, emerging category, it is on the rise and utilized by companies to make sense of their data streams. Users can leverage stream analytics tools to analyze data transferred among a whole range of internet of things (IoT) endpoints and devices, including smart cars, machinery, or home appliances. Real-time data analysis is key when companies are looking to make sense of their data as it comes in and in cases where time is of the essence, such as retail companies looking to keep a constant and consistent record of their inventory across multiple channels.
It’s not just companies who are realizing the importance of this technology. Investors, too, are taking note.
Confluent, an event streaming platform for Apache Kafka, recently raised $250 million in a Series E funding round led by Coatue Management. The funding takes Confluent's valuation to $4.5 billion.
As for the reason for this large-scale funding, Confluent CEO Jay Kreps said, "Though new data technologies come and go, event streaming is emerging as a major new category that is on a path to be as important and foundational in the architecture of a modern digital company as databases have been."
Krep’s argument is supported by G2 data. As the chart below of the review count for G2’s stream analytics software category shows, reviews have seen a significant increase since 2016.
Open-source projects can lead to big money
Confluent is a great example of how companies can build on top of open-source solutions; Apache Kafka, the open-source streaming data project that LinkedIn built in 2011, serves as Confluent's distributed message queue. The Confluent platform provides a paid distribution of Kafka that extends the core feature set by adding modules for real-time analysis, application orchestration, and development.
As G2 review data (as well as Confluent's press release) makes clear, stream analytics can and is being used across industries, from financial services to retail to health care. As a big data tool capable of impacting companies big and small, it is important for the solution to be able to scale, and scale quickly.
"[Confluent] unlocks the business from a consumer viewpoint. Strong monitoring to understand the health of our streaming platform. Easy to scale from a technical point of view."
Analytics software comes in many flavors
When looking to work with data—like with music—it is critical to consider the importance of a conductor and understand how all the parts add up to the whole. Stream analytics is one of many kinds of analytics software that can help organizations better understand their data.
Matthew Miller is a research and data enthusiast with a knack for understanding and conveying market trends effectively. With experience in journalism, education, and AI, he has honed his skills in various industries. Currently a Senior Research Analyst at G2, Matthew focuses on AI, automation, and analytics, providing insights and conducting research for vendors in these fields. He has a strong background in linguistics, having worked as a Hebrew and Yiddish Translator and an Expert Hebrew Linguist, and has co-founded VAICE, a non-profit voice tech consultancy firm.