Product Engineering Architecture Ecosystem Use Cases Company Early Access
Rust × DuckDB · Distributed Data Fabric

Distributed data processing, built for modern analytics.

Arolium LLC develops MPP data processing software for ETL and SQL analytics. Our platform combines a Rust-native distributed runtime with vectorized query execution and is currently in early access.

Contact Us About Arolium LLC
MPPdistributed compute
ETLdata pipelines
SQLanalytics workloads
Early accessactive development
arolium — illustrative product preview

Arolium LLC · United States software company

Distributed data processingBusiness softwareTechnical services
Core Capabilities

Three pillars. One fabric.

ETL and analytics have lived in separate systems for too long. Arolium collapses the pipeline and the query engine into a single distributed runtime.

Elastic SQL Compute

DuckDB's vectorized kernels on every worker, stitched into an MPP fabric.

  • Distributed shuffle engineAlias-aware repartitioning drives distributed joins and aggregations — including self-joins and grouping sets.
  • Broad SQL supportDesigned for analytical SQL patterns including joins, aggregations, window functions, and CTEs.
  • Scale without rewritesThe same SQL interface is designed to support local development and distributed deployments.

Declarative ETL Pipelines

From CDC to lakehouse in one DAG — checkpointed, versioned, exactly-once.

  • Pipelines as codeSQL + YAML DAGs that live in git, review like code, and deploy in one command.
  • Common data systemsDesigned to work with databases, event streams, object storage, and open table formats.
  • Incremental processingCheckpointed state and idempotent sink design support reliable pipeline execution.

Rust-Native Reliability

A memory-safe implementation focused on predictable resource use and operational simplicity.

  • Memory-safe foundationRust provides memory-safety guarantees without a garbage-collected runtime.
  • Replicated control planeThe architecture is designed to keep coordination metadata available during node failures.
  • Simplified deploymentA compact runtime is intended to reduce the number of moving parts in production.
Engineering Focus

Built around efficient execution.

The product is under active development. Our current engineering work focuses on correctness, distributed execution, and efficient use of compute and memory.

  • Vectorized executionColumnar processing is designed to improve analytical query efficiency.
  • Distributed data movementPartitioning and pruning are designed to reduce unnecessary network transfer.
  • Correctness before claimsPerformance results will be published with reproducible methodology after validation.
Product statusEarly access
01Core runtime

Distributed planning, execution, and coordination.

02Data pipelines

Declarative ingestion and transformation workflows.

03Validation

Correctness, reliability, and performance testing.

Arolium is not yet generally available. Features and implementation details may change during early access.
Architecture

One engine. Two topologies.

A Raft-replicated control plane schedules work onto stateless workers. Run compute next to NVMe for the hottest paths, or float it over object storage and scale to zero.

Mode 01 · Co-located

Compute beside NVMe

Workers own local storage for the hottest tables. Zero network hops on the critical path — the lowest latency an MPP topology can give you, for customer-facing analytics.

Mode 02 · Disaggregated

Stateless over object storage

Workers are designed to keep only cached state while reading from object storage, allowing compute capacity to expand or contract with workload demand.

Ecosystem

At home in your data stack.

Arolium sits at the center — ingesting from the systems you run, serving the tools your teams already love.

Ingest from

Kafka · Redpanda PostgreSQL CDC MySQL CDC S3 · GCS · Azure Iceberg · Parquet HTTP · Webhooks
Arolium AROLIUM ETL + COMPUTE

Serve to

Iceberg tables Superset · Metabase Grafana Arrow Flight SQL AI agents · MCP Webhooks

PLANNED INTEGRATIONS · OPEN DATA FORMATS · ARROW-NATIVE PROCESSING

Use Cases

Designed for data-intensive workloads.

01

Customer-facing analytics

Support interactive analytics applications with distributed SQL execution and columnar processing.

interactive SQLanalyticsdistributed compute
02

Streaming ETL & CDC

Move and transform operational data into analytical storage using checkpointed pipeline workflows.

incrementalCDCpipelines
03

Lakehouse compute

Process open table and file formats in object storage for reporting, transformation, and analysis.

IcebergParquetobject storage
04

AI data engineering

Prepare analytical and machine-learning datasets through repeatable transformation workflows.

data preparationtransformsworkflows
Company

Software and services from Arolium LLC.

Arolium LLC is a U.S.-registered technology company developing distributed data processing and analytics software for business customers.

Data processing software Software for distributed ETL, analytical SQL, and data pipeline workloads. Ask about the product → Business data teams Designed for companies building analytics platforms and data-intensive applications. Discuss a use case → Direct software sales Planned revenue from software subscriptions, product support, and related technical services. Contact sales → Contact Arolium LLC Product, partnership, and early-access inquiries. hello@arolium.com →
Early Access

Talk with our team.

Arolium is currently in active development. Contact Arolium LLC to discuss product evaluation, technical services, or early access.

Email hello@arolium.com Company information