HPCC Systems

What HPCC Systems does

HPCC Systems is an open-source, enterprise big data analytics platform developed and maintained by LexisNexis Risk Solutions (a division of RELX). Development began at LexisNexis in late 1999, and the platform was open-sourced in 2011. It is headquartered in Alpharetta, Georgia, with an operating team of 51-100 employees.

The platform's core architecture consists of two processing engines: Thor (a master/slave batch processing data-lake engine analogous to Apache Spark, scaling from a single node to thousands of nodes) and ROXIE (a peer-to-peer real-time query engine exposing REST/SOAP endpoints). Workloads are written in ECL (Enterprise Control Language), a proprietary high-level data-centric language that compiles into optimized data flow graphs, eliminating manual parallelization. Additional components include the Dali metadata server, the ECL IDE, ECL Watch for monitoring, the WsSQL JDBC connector, and a Machine Learning Library supporting ML and causality analytics. The platform supports both bare-metal and cloud-native deployment, with containerized Kubernetes/Helm packaging available on Azure, AWS, Docker Desktop, and Minikube.

HPCC Systems operates as a freemium, fully open-source product: the platform, training, and six months of support are free. There are no disclosed standalone revenue figures or external funding rounds; the platform's economic value is absorbed within LexisNexis Risk Solutions' insurance and legal data analytics businesses, where it processes petabyte-scale data libraries. Go-to-market is community-driven — developer forums, free online training courses, GitHub, YouTube, summits, and an academic program including Brazil-based initiatives since 2019. Primary customer segments are the insurance industry (fraud detection, risk assessment, claims analysis) and legal industry (research, due diligence, document processing), with enterprise data analytics and academic research as secondary segments. The platform has been in productive development for over 20 years and has accumulated thousands of deployments.

Name

HPCC Systems

Legal name

LexisNexis Risk Solutions

Website

https://hpccsystems.com

Company type

Private

Founded year

1999

Operating status

Operating

Headcount range

51–100 employees

Short description

HPCC Systems is an open-source big data analytics platform built and maintained by LexisNexis Risk Solutions. It provides batch and real-time data processing via its proprietary ECL language for insurance, legal, and enterprise data lake workloads.

Ownership category

akta.pro rank

Product category

Big Data Analytics Platform

NAICS

Computer Systems Design and Related Services (5415), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821)

SIC

Services-Prepackaged Software (7372), Services-Computer Programming, Data Processing, Etc. (7370)

akta.pro primary industry

HPC Clusters & Scale-Out Compute (x86/ARM) (HDACAOAB)

akta.pro secondary industries

HPC System Software & Resource Management (Schedulers, MPI, OS Images) (HDACAOAH), HPC Storage & Parallel File Systems (Lustre/GPFS/Object) (HDACAOAF), HPC-as-a-Product / On-Prem Managed HPC (Integrated Hardware + Ops) (HDACAOAK), HPC Supercomputers & Turnkey Systems (HDACAOAA)

Keywords

• Open source big data
• Data lake analytics
• Cluster computing platform
• Real-time query engine
• Enterprise data engineering

Headquarters

HQ city

Alpharetta

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Infrastructure, Marketing or Sales, Operations

Revenue model

1. Open Source Platform Distribution: HPCC Systems is completely free and open source. The platform is distributed without charge, with free training and six months of support included. Revenue is generated indirectly through LexisNexis Risk Solutions' internal use and enterprise deployments that support their core data analytics business.

Pricing tiers

Distribution channels5 records

Marketing channels8 records

Core offering

HPCC Systems provides an open-source, enterprise-ready big data analytics platform built around two core processing engines — Thor for batch data processing and ROXIE for real-time query delivery — programmed in ECL (Enterprise Control Language). The platform supports bare-metal, Docker, and Kubernetes-native containerized deployments on Azure and AWS, and ships with integrated machine learning, developer tooling (ECL IDE, ECL Watch, ECL Playground), SQL connectivity via WsSQL, and free training.

Product overview

HPCC Systems is a unified big data analytics platform consisting of a core platform and multiple integrated modules. The platform centers on two processing engines: Thor for batch data processing and ROXIE for real-time query delivery. Users write code in ECL (Enterprise Control Language), a high-level data-centric programming language. The platform supports multiple deployment options including bare metal, cloud native (Kubernetes), Docker containers, and cloud providers like Azure and AWS. Developer tools include the native ECL IDE, Visual Studio Code ECL extension, and ECL Watch for monitoring. Additional offerings include the Machine Learning Library for analytics, training courses, and Helm charts for Kubernetes deployment. The platform became open source in 2011 and has been in productive development for over 20 years.

Differentiator

Problem solved

Functional benefit

Brands

• Thor: The batch-oriented data processing engine (similar in functionality to Apache Spark) that handles data ingestion, transformation, cleaning, normalization, aggregation, and learning processes.
• ROXIE
• ECL (Enterprise Control Language)
• ECL Watch

Products and services

• HPCC Systems Platform Enterprise-grade open-source big data analytics platform purpose-built for high-speed data engineering. Combines Thor (batch) and ROXIE (real-time) engines, supports bare-metal and Kubernetes-native cloud deployments, and targets enterprise data lakes at petabyte scale.
• Thor Batch Processing Engine Batch-oriented data processing engine similar in functionality to Apache Spark. Handles data ingestion, transformation, cleaning, normalization, aggregation, and social network graph creation, scaling from a single node to thousands of nodes via master-slave architecture.
• ROXIE Real-Time Query Engine Real-time query delivery engine providing low-latency responses to queries. Delivers data to end users in real-time or batch mode, exposing services as REST or SOAP endpoints over a peer-to-peer architecture.
• ECL (Enterprise Control Language) Proprietary, high-level, data-centric programming language for parallel processing on massive datasets. ECL compiles into optimized data flow graphs where each node represents a data operation, eliminating manual parallelization.
• HPCC Systems Cloud Native Platform Containerized deployment of HPCC Systems on Kubernetes, enabling cloud deployments on Azure AKS, AWS EKS, and other Kubernetes providers with on-demand service scaling and resource optimization.
• HPCC Systems Machine Learning Library Bundle of machine learning algorithms for use with ECL, enabling predictive analytics, clustering, and causality analytics on big data.
• ECL IDE Native integrated development environment for ECL programming with code editing, debugging, and workunit submission capabilities for Windows-based development.
• ECL Playground Online browser-based environment at play.hpccsystems.com for trying ECL code with sample datasets without requiring local installation.
• Play Cluster Free, always-available cloud cluster for testing and learning HPCC Systems, providing access to Thor and ROXIE environments without local setup.
• WsSQL (JDBC Connector) HPCC Systems JDBC connector enabling SQL-based access to HPCC Systems data and queries from external applications.
• HPCC Systems Training Courses Free online courses covering introductory and advanced ECL programming, platform administration, ROXIE query development, and machine learning with ECL, taught by the platform's senior instructor.
• Helm Charts for HPCC Systems Kubernetes Helm charts for deploying HPCC Systems on cloud environments, available in the HPCC Systems Helm repository for simplified cloud deployment.

Quantifiable outcome

• Better performance than Apache Spark on aggregation operations, with HPCC Systems outperforming Spark on aggregate by Key and aggregate by integer operations
• +2 more outcomes

Named customers2 records

Segments4 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration5 records

AI capability4 records

Feature7 records

Scale indicators3 records

Recent moves7 records

Expansion highlights5 records

Direct peers

• Apache Spark: The dominant open-source distributed data processing engine. HPCC Systems' Thor engine is directly compared to Spark in terms of batch processing functionality, scalability, and performance on aggregation workloads.
• Databricks: The commercial unified analytics platform built on Apache Spark. Databricks competes directly in the open-source big data space with a managed lakehouse architecture and broader enterprise tooling.
• Cloudera: Provider of enterprise data cloud and analytics platform built on Hadoop/Spark. Competes with HPCC Systems for enterprise big data and data lakehouse deployments, particularly in regulated industries.
• Apache Hadoop: The foundational open-source framework for distributed storage and processing. HPCC Systems positions itself as an integrated alternative to the Hadoop/HDFS/MapReduce stack with a unified data-lake platform.
• Apache Flink: Open-source stream processing framework for real-time analytics. Overlaps with HPCC Systems' ROXIE real-time query engine in the real-time/batch hybrid processing use case.

Emerging players

• Dremio: Open data lakehouse platform providing SQL-based query access to data lake storage. Competes with HPCC Systems' ROXIE engine for real-time analytics and self-service data access on cloud data lakes.
• Trino (formerly PrestoSQL): Distributed SQL query engine for big data analytics across data lakes and warehouses. Overlaps with HPCC Systems in the high-performance query layer for large-scale data lake analytics.

Broad incumbents

• Snowflake: Cloud-native data warehouse and lakehouse platform serving enterprise analytics at massive scale. Competes indirectly for the same data engineering and analytics workloads as HPCC Systems, particularly in cloud deployments.
• Amazon EMR: AWS managed Hadoop/Spark service providing cloud-based big data processing. Competes with HPCC Systems' cloud-native platform for enterprise customers building data lakes on AWS.
• Google Cloud Dataproc: Managed Spark and Hadoop service on Google Cloud. Targets the same enterprise big data workloads as HPCC Systems with the added benefit of GCP integration and managed operations.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat5 records

Key risks6 records

Key highlights6 records

Customer concentration

• GitHubgithub.com/hpcc-systems
• YouTubeyoutube.com/user/HPCCSystems
• LinkedInlinkedin.com/company/hpcc-systems
• Instagraminstagram.com/hpcc_systems
• Xx.com/hpccsystems
• Facebookfacebook.com/hpccsystems

Revenue estimate

Valuation estimate

Number of profiles

Profiles9 records

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about HPCC Systems