QOMPLX announces their high-profile, cost-efficient time-series database Prometheus Integration

QOMPLXTM is happy to announce the inclusion in TimeEngine, QOMPLX's pioneering multidimensional database and analysis engine for the intakes and storage of time series data at scale of the popular and powerful systems monitoring/alerting toolset Prometheus. Even when you gather and operate billions of data events a day, TimeEngine facilitates improved understandings for customers.

Prometheus is an independent and well-received project with a very active developing and use community inspired and constructed by former Google and SoundCloud developers. Prometheus has become a vital tool in order to acquire real-time visibility in the computer and application architecture of production of next generation cloud organisations.

Today more than 600 companies, including Uber, Slack and Robinhood, employ Promeetheus in their tech stacks. But its operation on a scale has become a well-reported difficulty for many organisations.

"We're happy to offer the quick and scalable TimeEngine data analysis capabilities of the Prometheus-Toolkit to customers," Jason Crabtree, CEO of QOMPLX, remarked.

"There are sophisticated query tools and specific modelling capabilities for any Prometheus user to employ to deliver greater modelling capabilities, in conjunction with data analytics and retention costs optimisation"

This strategic integration with Prometheus is an icon of the unique role QOMPLX played in analytical streaming – fusion of operational, risk and financial infrastructure and data infrastructure. QOMPLX offers solutions that minimise important long-term hazards, including cyber safety, insurance and climate concerns, that are key to our modern global economy. The underpinning capacity of the QOMPLX data centre fuel cloud-native cyber security, operations and insurance risk analytics offering is far faster than usually seen in the industry to quickly absorb, convert and contextualise data.

The QOMPLX Vice President of Engineering Angad Salaria remarked, "TimeEngine adapter for Prometheus remote storage provides a smooth integration path for clients, so that scalability can be brought into their Prometheus base system.” " The versatile and multi-dynamic data model ofTimeEngine offers greater analytical time series capacities, and solves typical operational difficulties crucial to Prometheus' functioning in big contexts."

About Prometheus
Prometheus is a fast and user-friendly integrated monitoring toolset with powerful query language and data modelling features, inspired by Google's Borgmon, built at SoundCloud in 2012 and openly released in 2015. Prometheus monitoring clarifies systems and how to run them most efficiently, eliminates noise and sends customisable notifications only when severe problems have to be resolved. Prometheus is a controllable, trustworthy, web-free technology that avoids the chance of a waterfall. In order to obtain data from any client, the Prometheus Node Exporter can also be adapted. Prometheus is a software licenced by Apache 2 that is also a graduation project of the Cloud Native Computing Foundation.

About TimeEngine
QOMPLX's TimeEngine gives your risk a holistic and multidimensional perspective. It solves the ubiquitous need for arbitrary data sources and time-series measurements to be stored, indexed and served on a large scale. TimeEngine provides elastic autoscaling in the range of petabytes while keeping low query performance as a software as a service provider. It enables decision-making to be speededed up, sensor data detection and triage procedures to become automated and enormous business value to be created, through confidence and without interruption intakes, processing, storing and alerting analytical routines and queries. This may include applications such as:

• Tracking and altering the properties of movable goods like vehicles and containers
• Examination of how wind or flood exposures can affect company premises
• How operational technology assets function and improve performance over time through predictive maintenance and operational procedures
• Understanding climate change through the monitoring of animal migration or behaviour.
• Evaluating and alerting activity and geo-tagging information in vicinity to suspected terrorist objectives and events
• Analysis of trillions of sensor reports to model the performance of commercial buildings in a portfolio, class or area.

Multiple Languages — TimeEngine supports Java, Scala, Python, Erlang and Elixir client libraries and easily incorporates and selects external projects such as Prometheus and Kafka with a broader QOMPLX ecosystem for analysis tools.

About QOMPLX
QOMPLX assists enterprises with our powerful proprietary risk cloud with smart business choices and improved risk management. In order to assist enterprises better assess, model and anticipate risk, we are the leaders at the intake, transformation and contextualization of vast, complex and diverse data sources via our cloud-oriented data facility. Our specialist cybersecurity, insurance, and financial solutions are leading global companies and public sector mission critical agencies.