Hotrod

Hotrod is a distributed data processing system that simply and easily allows you to manipulate data that you send to your existing data analytics systems, SIEM or other data hungry applications, while at the same time reducing volume and increasing the value of that data.

It does so by supporting a distributed architecture which allows you to collect and process data as close to the data source as possible, combined with a feature rich and expressive language (pipes) that allows anyone to get data into the preferred (data analytics) systems without needing to be a developer or an expert.

The pipes language has been thoughtfully crafted using lessons learnt by Panoptix over more than a decade of working with distributed and high volume data analytics systems and seeing the challenges that can arise when faced with the dynamic nature of on-boarding new data sources.

pipes have built-in analytics capabilities that are available close to your data sources, and is the perfect companion to your existing data analytics systems.

Hotrod and the pipes language is simple enough to use frequently and regularly but still powerful enough to enable you to easily on-board even the most challenging data sources, thus enabling you to rapidly achieve maximum value out of your data analytics investments.

Hotrod Uses

  • Receiving and harvesting data from a diverse collection of data sources.

  • Reducing data volumes through clever manipulation of the format and layout of the data.

  • Enriching data to add the maximum amount of value possible in the shortest possible time.

  • Generating valuable data from legacy utilities and tools that generally require software development to integrate into existing data analytics systems.

Why another language?

pipes were born out of the experience of the founders building enterprise data analytics systems with products such as Splunk and Elasticsearch. It is the tool that we always wanted when doing those deployments.

There are many developer tools available to do integrate data into data analytics system but very few of these systems cater for administrators and analysts themselves.