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HPCC Systems

hpccsystems.com

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Spec score 8.7 #2 of 19 in Data Lake Software

What it is

HPCC Systems is a free, open-source platform for enterprise big-data processing and data-lake management. Its core components are ECL, a declarative and modular language, Thor for data refinement, and Roxie for data delivery. ECL's compiler optimizes programs for parallel processing and compiles them into C++. Thor handles ingestion, transformation, linking, and indexing; Roxie serves concurrent queries. Clusters can scale from two computers to more than a thousand commodity-hardware nodes. The cloud-native platform runs on Kubernetes and supports Azure Kubernetes Service and Amazon Elastic Kubernetes Service. Storage options include AWS S3, Azure Blob Storage, AWS Elastic Block Store, Azure Files, and Azure Disks. Security capabilities include end-to-end encryption, service meshes, OAuth 2.0 with Azure AD support, JWT, and configurable controls for data and services. The Machine Learning Library offers ECL-accessible algorithms for building and testing prediction models. Integrations include Spark, Kafka, Couchbase, Redis, Memcached, Pentaho, R, JDBC, Java APIs, and Tableau data connectors. ESP exposes queries through XML, HTTP, SOAP, and REST interfaces, and deployed queries can be called with REST/JSON. The platform is free to use under the Apache 2.0 license and is self-hosted.

Spec sheet

What it does
HPCC Systems is an open-source, massively parallel platform for big-data processing, analytics, data lakes and data warehouses.Read 15 Oct 2026 · hpccsystems.com
Purpose
HPCC Systems is an open-source, data-intensive supercomputing platform for enterprise big-data problems.Read 30 Sep 2026 · hpccsystems.com
Integrations
Official integrations include Spark, Kafka, Couchbase, Redis, Memcached, Pentaho, R, JDBC, Java APIs and Tableau data connectors.Read 30 Sep 2026 · hpccsystems.com
Security
Cloud-native security features include end-to-end encryption, Linkerd or Istio service meshes, OAuth 2.0 with Azure AD support, and JWT.Read 30 Sep 2026 · hpccsystems.com
License
The Community Edition is licensed under the Apache License 2.0.Read 15 Oct 2026 · github.com
Headquarters
Atlanta metropolitan area, Georgia, United StatesRead 28 Sep 2026 · hpccsystems.com
Founded
2000Read 28 Sep 2026 · hpccsystems.com
APIs
ESP exposes ECL queries through XML, HTTP, SOAP and REST interfaces, and deployed queries can be called with REST/JSON.Read 30 Sep 2026 · hpccsystems.com
Architecture
The platform includes the ECL programming language, Thor data-refinery engine, and Roxie data-delivery engine.Read 30 Sep 2026 · hpccsystems.com
Client operating systems
The ECL IDE runs on Windows, while client tools are available for Windows, Linux and macOS and container setup can be initiated from Windows, Mac or Linux terminals.Read 15 Oct 2026 · hpccsystems.com
Cloud deployment
The cloud-native platform runs on Kubernetes and supports Azure Kubernetes Service and Amazon Elastic Kubernetes Service.Read 30 Sep 2026 · hpccsystems.com
Cloud storage integrations
Cloud-native deployments support AWS S3, Azure Blob Storage, AWS EBS and Azure storage options.Read 15 Oct 2026 · hpccsystems.com
Company headquarters
LinkedIn lists HPCC Systems headquarters at Alpharetta, Georgia and identifies the organization as founded in 2011.Read 15 Oct 2026 · linkedin.com
Company origin
The independent ODBMS.org interview says development began in 1999 as an internal LexisNexis Risk Solutions system and the platform was open-sourced in 2011.Read 15 Oct 2026 · odbms.org
Company ownership
HPCC Systems is presented as a LexisNexis Risk Solutions project and is used as the foundation for many LexisNexis data products.Read 15 Oct 2026 · odbms.org
Current release
The download page identifies version 10.6 as the latest platform release.Read 15 Oct 2026 · hpccsystems.com
Data lake
HPCC Systems is a dedicated end-to-end data-lake management platform for combining mixed-schema data.Read 30 Sep 2026 · cdn.hpccsystems.com
Documentation depth
Documentation includes administrator, programmer, installation, containerized-platform, WsSQL, configuration and release-note materials.Read 15 Oct 2026 · hpccsystems.com
ECL
ECL is a declarative, modular language whose compiler optimizes code for parallel processing and compiles it into C++.Read 30 Sep 2026 · hpccsystems.com
ECL language
ECL is a declarative, data-oriented language that lets developers describe computations while the platform determines execution details.Read 15 Oct 2026 · hpccsystems.com
Encryption
ECL can encrypt output data with 256-bit AES and compress it with LZW before serialization.Read 15 Oct 2026 · hpccsystems.com
Independent feature coverage
Business-Software.com lists LDAP or Active Directory integration, thousands of nodes, high availability, monitoring, graphical configuration and collaborative source control.Read 15 Oct 2026 · business-software.com
Independent pricing finding
Business-Software.com reports that pricing requires contacting the vendor directly.Read 15 Oct 2026 · business-software.com
JDBC support
The platform offers an HPCC JDBC driver and WsSQL as SQL access options, each supporting a subset of SQL.Read 15 Oct 2026 · hpccsystems.com
Known output limit
The ECL Programmer's Guide documents a deliberate failure when returning more than 10 MB of result data directly to a workunit.Read 15 Oct 2026 · cdn.hpccsystems.com
Kubernetes deployment
The containerized edition runs on Kubernetes and supports Helm, Terraform, Amazon EKS and Azure AKS deployments.Read 15 Oct 2026 · hpccsystems.com
Language extensibility
ECL can embed or call Java, JavaScript, Python, R, C++, MySQL, SOAP services, command-line programs and external plugins.Read 15 Oct 2026 · hpccsystems.com
Limit: operational complexity
Business-Software.com characterizes the delivery system as complex even though it is designed for rigorous service levels and low latency.Read 15 Oct 2026 · business-software.com
Limit: pricing transparency
The independent product listing provides no public amount and directs buyers to contact the vendor for pricing.Read 15 Oct 2026 · business-software.com
Machine learning
The supplied machine-learning library includes algorithms such as DBSCAN, K-means, regression, neural networks and learning trees.Read 15 Oct 2026 · hpccsystems.com
Operating systems
A current supported Linux system is required for a single-node cluster; ECL IDE is available for Windows and only client tools are supported on Apple OSX.Read 30 Sep 2026 · hpccsystems.com
Praise: end-to-end scope
An ODBMS.org interview describes HPCC Systems as covering ingestion, ETL, product-data creation and end-user delivery in one platform.Read 15 Oct 2026 · odbms.org
Praise: performance
The same independent interview reports a complex job falling from about 28 hours on an IBM mainframe to roughly 6.5 minutes with ECL on the predecessor platform.Read 15 Oct 2026 · odbms.org
Processing
Thor performs ingestion, transformation, linking and indexing, while Roxie serves high-performance concurrent queries.Read 30 Sep 2026 · hpccsystems.com
Public repositories
The HPCC Systems GitHub organization lists 168 public repositories, including the platform, Helm charts, Java APIs and developer tools.Read 15 Oct 2026 · github.com
Recent release note
Community Edition 10.0.82-1 was released on August 5, 2026 and included an AES-encryption regression fix and a build fix for builds without OpenLDAP.Read 15 Oct 2026 · hpccsystems.com
Roxie engine
Roxie is the data-delivery engine designed to serve very large numbers of concurrent end-user queries.Read 15 Oct 2026 · odbms.org
Scale
Clusters can scale from two computers to more than a thousand commodity-hardware nodes.Read 30 Sep 2026 · hpccsystems.com
Security controls
Configurable security managers govern identities and access to landing zones, files, metadata, workunits and ESP services.Read 15 Oct 2026 · hpccsystems.com
Self-hosting
Users can deploy HPCC Systems on their own Linux nodes, bare-metal clusters or Kubernetes infrastructure.Read 15 Oct 2026 · hpccsystems.com
Storage
The cloud-native storage plane supports AWS S3, Azure Blob Storage, AWS Elastic Block Store, Azure Files and Azure Disks.Read 30 Sep 2026 · hpccsystems.com
Support and training
HPCC Systems provides public Stack Overflow community support, free online tutorials and free online training.Read 30 Sep 2026 · hpccsystems.com
System requirements
A single-node installation requires a current supported Linux system; the FAQ states a 4 GB minimum per node and commodity hardware support.Read 15 Oct 2026 · hpccsystems.com
Third-party integrations
HPCC Systems provides plugins, connectors, embedded-language support and external-datastore integrations.Read 15 Oct 2026 · hpccsystems.com
Thor engine
Thor is the platform's distributed data-refinement engine for large-scale preprocessing.Read 15 Oct 2026 · odbms.org
Training and support
Free online courses, videos, community resources and optional remote or on-site training are available.Read 15 Oct 2026 · odbms.org
Virtual-machine limit
The documentation says version 8.2.0 was the final release with an official VirtualBox VM image, with later local use moving to containers.Read 15 Oct 2026 · hpccsystems.com
Web protocols
WsSQL accepts HTTP or HTTPS requests through SOAP or REST interfaces.Read 15 Oct 2026 · cdn.hpccsystems.com
WsSQL API
WsSQL exposes HPCC logical files as relational tables and published queries as stored procedures through an SQL interface.Read 15 Oct 2026 · cdn.hpccsystems.com

Plans and prices

Community Edition Free free download server platform · ECL · IDE · client tools · documentation · graph control Read 15 Oct 2026 · business-software.com
Open source Free free to use · Apache 2.0 licensed · self-hosted Read 30 Sep 2026 · cdn.hpccsystems.com
Enterprise subscription Priced on request contact vendor software · services · professional training support Read 15 Oct 2026 · business-software.com

Every HPCC Systems plan and price →

Strong points and limits

Strong points

  • Free to use under the Apache 2.0 license.
  • Clusters can scale beyond a thousand nodes.
  • Includes separate data-refinery and data-delivery engines.
  • Supports Kubernetes and multiple cloud storage options.

Limits

  • A supported Linux system is required for a single-node cluster.
  • ECL IDE is available for Windows.
  • Apple OSX supports client tools only.

Who it suits

HPCC Systems suits organizations with enterprise big-data workloads that need data-lake management and parallel processing. It may fit teams prepared to work with ECL and self-hosted deployments.

HPCC Systems in depth

Read the full write-up

Overview

HPCC Systems is an open-source platform for organizations that need to manage and process large, mixed-schema datasets across a cluster. It suits data engineering teams comfortable running self-hosted infrastructure and writing ECL; its combination of refinement and query serving is compelling, but it is not a turnkey managed service.

Its architecture pairs ECL, a language for describing data work, with Thor for data preparation and Roxie for query delivery. The software is Apache 2.0 licensed and free to use. For more options, browse our Data Lake Software directory.

Key features

Declarative processing with ECL

ECL is modular and declarative, and its compiler optimizes programs for parallel processing before compiling them into C++. That gives teams a way to express data-intensive work for cluster execution, but it requires a programming-led approach rather than a no-code workflow.

Refinement and query delivery

Thor handles ingestion, transformation, linking and indexing; Roxie serves concurrent queries. Keeping large preparation jobs and query serving in separate engines gives one platform a role across the data-lake pipeline.

Cluster and cloud scale

Clusters can span from two computers to more than a thousand commodity-hardware nodes. The cloud-native platform runs on Kubernetes, including Azure Kubernetes Service and Amazon Elastic Kubernetes Service, and supports storage in AWS S3, Azure Blob Storage, AWS Elastic Block Store, Azure Files and Azure Disks. This range supports substantial deployment flexibility, though operating the platform remains the user's responsibility.

Security, machine learning and integrations

Cloud-native security features include end-to-end encryption, Linkerd or Istio service meshes, OAuth 2.0 with Azure AD support and JWT. Configurable security managers can control access to landing zones, file scopes, recordset data, workunit execution and ESP services. The Machine Learning Library provides ECL-accessible algorithms for building and testing qualitative or quantitative prediction models.

Official integrations include Spark, Kafka, Couchbase, Redis, Memcached, Pentaho, R, JDBC, Java APIs and Tableau data connectors. ESP exposes ECL queries through XML, HTTP, SOAP and REST interfaces; deployed queries can also be called with REST/JSON. That breadth is useful where a data platform must connect to existing tools and applications.

Pricing

Open source: free. The plan is free to use, Apache 2.0 licensed and self-hosted. It avoids a software license charge, but does not remove the work of providing infrastructure and running the deployment.

There are no paid HPCC Systems plans described here. Its free option is best suited to teams that can operate their own platform; organizations seeking a managed service or vendor-priced support arrangement should compare other products.

Platforms

HPCC Systems supports Linux, macOS, Windows, web, API, extension and self-hosted platforms. A current supported Linux system is required for a single-node cluster. The ECL IDE is available for Windows, while Apple OSX supports client tools only; macOS should therefore not be mistaken for a supported cluster host. The deployment model is hybrid.

The platform supports both ingestion modes, both query interfaces, data sharing, a metadata catalog and governance controls. Public Stack Overflow community support, free online tutorials and free online training provide routes for teams learning to operate and use it.

Who it's for

HPCC Systems is a strong fit for organizations building a data lake around large-scale processing and concurrent query delivery, especially those that want open-source licensing, broad integrations and control over deployment. It is less suitable for teams without Linux and cluster operations capacity, or for users who want a managed platform instead of self-hosting.

Pros and cons

Pros: One platform covers data ingestion and refinement through query serving, with Thor and Roxie assigned distinct roles.

Pros: Apache 2.0 licensing and a free plan let teams use the software without a license fee.

Pros: Kubernetes deployment, multiple cloud storage options and a wide set of integrations give teams flexibility in fitting it into a data stack.

Cons: Self-hosting and the Linux requirement for a single-node cluster make infrastructure operations part of the adoption cost.

Cons: ECL's programming model is a poor fit for teams looking to prepare and query data without writing specialized code.

Cons: On macOS, only client tools are supported, not cluster operation.

Alternatives

AWS Lake Formation is worth considering if you want a paid product with a free plan and free permission creation through integrated services; standard usage rates apply for integrated services such as Amazon S3.

Apache Ozone is another free, Apache License 2.0 option, with API, Linux, web and self-hosted platforms.

Apache Hadoop HDFS is a free, open-source alternative with Linux, Windows, API and self-hosted support.

HPE Ezmeral Data Fabric offers a paid product with a free plan and free trial; its software pricing varies by reseller.

lakeFS has a free plan and trial, with enterprise pricing by contact and managed cloud or self-managed deployment options.

Oracle Big Data Service is a paid cloud option with a free trial; its service fee is priced on request, billed per OCPU per hour, with compute shapes and Oracle Cloud SQL priced separately.

Qubole provides a full-featured 30-day free trial and a paid Enterprise Edition, making it an option for readers who want to evaluate a paid product before committing.

Unilake is a free platform licensed under AGPL 3.0 and EUPL that can run fully isolated in an environment of the user's choice.

Verdict

Choose HPCC Systems if your team needs an open-source data-lake platform that can refine large datasets and serve concurrent queries at cluster scale, and has the skills to run it. Its strongest argument is the combination of free Apache 2.0 software with a broad processing and integration stack. Look elsewhere if self-hosting, Linux operations or ECL development do not fit your team.

Verdict

HPCC Systems combines data-lake management, scalable processing, and query serving in a self-hosted open-source platform. Check the operating-system requirements and deployment model against your infrastructure.

Where Specifiction places it

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