QOMPLX Announces Prometheus Integration for its High-Performance, Cost-Efficient Time Series Database

Prometheus users can directly leverage the powerful capabilities of TimeEngine to simplify large-scale data processing & gain real-time risk management insights

Tysons, Virginia, UNITED STATES

TYSONS, Va., July 08, 2021 (GLOBE NEWSWIRE) -- QOMPLX™ is proud to announce the integration of the popular and powerful systems monitoring & alerting toolkit Prometheus with TimeEngine, QOMPLX’s groundbreaking multidimensional database and analytics engine for ingesting, storing, and modeling time series data at scale. TimeEngine makes it easy for customers to better understand their data, even when collecting and operating at billions of data events per day.

Inspired and built by former Google and SoundCloud engineers, Prometheus is a widely adopted standalone project with a highly active developer and user community. Prometheus has become an especially critical tool for next-generation cloud native companies seeking to gain real-time visibility into production computing and application infrastructure. 

Today over 600 companies use Prometheus in their tech stacks, including Uber, Slack, and Robinhood - but operating it at scale has become a well-documented challenge for numerous organizations.

“We are incredibly excited to offer customers the fast and scalable data analytics capabilities of TimeEngine integrated within the Prometheus toolkit,” said QOMPLX CEO Jason Crabtree. “Any Prometheus user will be able to leverage TimeEngine’s powerful querying tools and specialized modeling capabilities to provide superior modeling capabilities alongside optimization of data analysis and retention costs."   

This strategic integration with Prometheus is emblematic of QOMPLX’s unique role in streaming analytics - the fusion of operational, risk, finance and data infrastructure. QOMPLX provides solutions to mitigate major long-term risks that are foundational to our modern global economy, including cybersecurity, insurance, and climate with spatio-temporal challenges. The underlying capabilities of the QOMPLX core data factory fuel cloud-native cybersecurity, operations, and insurance risk analytics offerings with the ability to rapidly ingest, transform and contextualize data at scale, much faster than traditionally seen across the industry.

“TimeEngine’s adapter for Prometheus remote storage provides an effortless integration path for customers to bring TimeEngine’s scalability into their Prometheus based environment,” said QOMPLX Vice President of Engineering Angad Salaria. “TimeEngine’s flexible and multi-dimensional data model provides superior time-series analysis capabilities while solving common operational challenges critical to running Prometheus in large scale environments.”

About Prometheus
Inspired by Google’s Borgmon, written at SoundCloud in 2012, and publicly launched in 2015, Prometheus is an efficient and user-friendly inclusive monitoring toolkit with powerful query language and data modeling capabilities. Prometheus monitoring provides clarity into systems and how to most effectively run them, eliminating noise and only sending fully customizable alerts when major issues need to be solved. Prometheus is a manageable and reliable system that does not depend on the internet and eliminates the potential for cascading failure. Further, the Prometheus Node Exporter can be adjusted to retrieve data from any client. Prometheus is an Apache 2 licensed software tool which is also a Cloud Native Computing Foundation graduated project.

About TimeEngine
QOMPLX's TimeEngine provides a multidimensional and holistic view of your risk. It addresses the common need to store, index, and serve metrics from arbitrary event and time series data sources at substantial scale. TimeEngine supports elastic autoscaling to petabyte ranges while maintaining low millisecond-level query performance available as a Software-as-a-Service offering. This capability enables the acceleration of decision-making, the automation of detection and triage routines on sensor data as well as the creation of tremendous business value by ingesting, processing, storing, and alerting on analytic routines and queries with confidence and without interruption. That can include applications like:  

  • Tracking mobile assets like vehicles and shipping containers and how their attributes are changing
  • Examining how corporate premises may be impacted by wind or flood exposures
  • How operational technology assets perform over time and can achieve better performance using predictive maintenance and operations practices
  • Understanding climate change by tracking changing animal migrations or behaviors
  • Evaluating and alerting on activities and geo-tagged information within a specified proximity to potential terrorism targets and political violence events
  • Analyzing billions of sensor reports to model commercial building energy performance within a portfolio, usage class, or geography 

Multiple Languages - TimeEngine provides client libraries for Java, Scala, Python, Erlang and Elixir and integrates seamlessly with the larger QOMPLX ecosystem of risk analysis tools and select external projects such as Prometheus and Kafka.


QOMPLX helps organizations make intelligent business decisions and better manage risk through our advanced, proprietary risk cloud. We are the leaders at rapidly ingesting, transforming, and contextualizing large, complex, and disparate data sources through our cloud-native data factory in order to help organizations better quantify, model, and predict risk.  Our specialized experts and technology solutions in cybersecurity, insurance, and finance power leading global corporations and mission critical public sector agencies. For more information, visit qomplx.com and follow us @QOMPLX on Twitter. 

James Faeh, Director of Corporate Communications