Team brings deep experience in distributed systems, big data integration and machine learningNEW YORK – (BUSINESS WIRE) – Datadog, the leading SaaS-based monitoring platform for cloud applications, today announced it has acquired Mortar Data, a New York-based startup enabling companies to build and run custom big data applications and data pipelines. With the addition of Mortar Data’s analytics platform and experienced team, this acquisition will extend Datadog’s data analytics capabilities and will soon provide Datadog users with new ways to gain actionable insights from their data.
“Mortar Data has built a sophisticated and highly scalable platform for analyzing massive amounts of data,” said Olivier Pomel, co-founder and CEO of Datadog. “As Mortar Data’s customers we have already been using many of their capabilities. We look forward to using the Mortar Data platform, and the team’s analytics and machine learning expertise, to provide our customers with unique, actionable insights on the hundreds of billions of data points we gather each day.”
Mortar Data’s platform allows users to analyze data and build big data apps with ease. Mortar users can integrate different data sources via robust pipelines and perform complex analyses with custom machine learning applications. The platform accelerates the development and deployment of data projects and then provides operational support by quickly pinpointing issues in production and automatically recovering from transient problems.
“Over the past few years, Datadog has rapidly grown to become the leader in the cloud monitoring space,” said K Young, CEO of Mortar Data. “It became increasingly apparent that together we could accomplish something truly great by making our platform the analytics engine for the massive amounts of performance data that Datadog gathers. Our team is looking forward to joining forces with Datadog, and providing unique capabilities that will help customers quickly find and fix performance anomalies across cloud applications that run at scale.”
“In an IT operations analytics (ITOA) context, machine learning is a crucial addendum to big data platforms and services since it allows for the automated generation of insights into high volume, highly volatile, and highly heterogeneous datasets – insights that would, in most cases, be unavailable without the automated assist,” wrote Will Cappelli, Research VP, Enterprise Management, Gartner.*
Most recently, Datadog announced a $31M Series C funding round led by existing investor Index Ventures. The company continues to strengthen its leadership position within the market and has seen tremendous year-over-year growth since launching in 2010, adding customers such as Netflix, EA, Spotify, MercadoLibre and AdRoll.
- Company Blog (https://www.datadoghq.com/blog/)
- Twitter: @datadoghq (https://twitter.com/datadoghq)
- GitHub (https://github.com/datadog)
About DatadogDatadog is a monitoring service that brings together data from servers, databases, applications, tools and services to present a unified view of the applications that run at scale in the cloud. These capabilities are provided on a SaaS-based data analytics platform that enables Dev and Ops teams to work collaboratively on the infrastructure to avoid downtime, resolve performance problems and ensure that development and deployment cycles finish on time. Media Contact Mindshare PR Heather Fitzsimmons firstname.lastname@example.org (650) 800-7160
*Gartner, Add New Performance Metrics to Manage Machine-Learning-Enabled Systems Will Cappelli, 04 November 2014