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HPCC Systems vs Parseable

HPCC Systems

hpccsystems.com

Parseable

parseable.com

Side by side

FigureHPCC SystemsParseable
Price fromFree$0.39/mo
Free planYesYes
Free trial—Yes
Open sourceYes—
WebYesYes
WindowsYesYes
macOSYes—
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published33
Spec score · Data Lake Software8.7 (#2)8.1 (#5)
ArchitectureThe platform includes the ECL programming language, Thor data-refinery engine, and Roxie data-delivery engine.The product is written in Rust and uses an object-store-native, open columnar format.
HeadquartersAtlanta metropolitan area, Georgia, United StatesSan Francisco, California, United States
IntegrationsOfficial integrations include Spark, Kafka, Couchbase, Redis, Memcached, Pentaho, R, JDBC, Java APIs and Tableau data connectors.The site lists integrations including Prometheus, Grafana, Kafka, Redpanda, AWS, Azure, OpenTelemetry, Kubernetes, Fluent Bit, Fluentd, Vector, MinIO, OpenAI, and Anthropic.
SecurityCloud-native security features include end-to-end encryption, Linkerd or Istio service meshes, OAuth 2.0 with Azure AD support, and JWT.The site identifies Parseable as GDPR certified and SOC 2 Type II.

Plans

HPCC Systems

  • Community EditionFree
  • Open sourceFree
  • Enterprise subscriptionPriced on request

HPCC Systems pricing →

Parseable

  • OSSFree
  • Cloud$0.39 a month
  • Enterprise$15,000 a year

Parseable pricing →

In their own words

HPCC Systems

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.

Visit hpccsystems.com

Parseable

Parseable is an open observability platform for logs, metrics, and distributed traces. Its features include dashboards, alerts, service maps, error pages, and root-cause analysis. Users can query telemetry with SQL or natural language, and use forecasting and AI analysis. Written in Rust, it uses an open columnar format designed for object storage. Deployment choices include self-hosted open source, managed cloud, and enterprise deployments with bring-your-own-cloud options. Listed integrations include Prometheus, Grafana, Kafka, Redpanda, AWS, Azure, OpenTelemetry, Kubernetes, Fluent Bit, Fluentd, Vector, MinIO, OpenAI, and Anthropic. Its MCP connects AI agents to live telemetry through structured tools, and its Slack bot brings operational answers into Slack. The free OSS plan includes SQL queries, dashboards, threshold alerts, OIDC SSO, unlimited users, and customizable retention and object storage. OSS supports only one query node and lacks groups for RBAC. Cloud costs $0.39 per month, billed per GB ingested, and includes 365 days of retention and a 14-day trial. Enterprise starts at $15,000.00 per year.

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