Coordinate Data Workflows Across Distributed Systems
Automate, sequence, and control data workflows across cloud, on-prem, and edge environments so every system receives the right data, in the right order, at the right time
The Data Orchestration Problem
Modern data stacks span dozens of systems, environments, and execution layers. Orchestration determines whether those systems work together—or fail independently.
Fragmented workflows
Scattered Execution Logic
Data pipelines span ingestion tools, stream processors, transformation jobs, and downstream platforms. Execution logic is scattered across scripts, schedulers, and custom glue code. Context is lost between steps.
Unreliable execution timing
Dependency Failures
Jobs trigger before dependencies are ready or after conditions have already changed. Missed signals, partial runs, and out-of-order execution create inconsistent downstream state. Typical recovery requires manual replays and backfills.
Operational blind spots
Black-Box Pipelines
Failures occur inside black-box pipelines. Teams lack visibility into what ran, what didn't, and why. Mean time to resolution stretches from minutes to hours.
High orchestration overhead
25-45% Engineering Time Lost
Custom DAGs, cron jobs, and workflow scripts break under schema changes, scaling events, or network interruptions. Engineering teams spend 25–45% of their time maintaining orchestration logic instead of improving data reliability.
Expanso Orchestrates Data Where It Runs
Coordinate data workflows across distributed environments, enforcing execution order, conditions, and recovery logic at the point of data movement
How Expanso Orchestrates Data
Connect across environments
Universal Compatibility
Coordinate workflows spanning databases, streams, APIs, SaaS tools, and edge systems. One orchestration model works across cloud, on-prem, and hybrid deployments.
Sequence and coordinate execution
Dependency-Aware
Define dependencies, triggers, and conditions directly in the data flow. Jobs run only when prerequisites are met—no premature execution, no stale state.
Handle failure automatically
Self-Healing
Built-in buffering, retry, checkpointing, and recovery logic keep workflows running through network drops and partial outages. No manual restarts. No fragile backfills.
Enforce policy during execution
Inline Compliance
PII, GDPR, HIPAA, and financial controls are enforced as workflows run—not after the fact. Execution, lineage, and compliance stay consistent across thousands of coordinated tasks.
Observe every workflow
Full Visibility
End-to-end visibility into pipeline state, execution timing, failures, and downstream impact. Operators see exactly where workflows slow, stall, or break.
Outcomes From Your Data Orchestration Platform
Real impact across distributed systems and data pipelines
More reliable pipeline execution across distributed systems
Reduction in failed or partially executed workflows
Deterministic execution order across dependent systems
Less engineering time spent maintaining orchestration scripts and schedulers
Real-World Impact
See how leading organizations orchestrate data workflows at scale
Coordinating Live Data Across 23 Stadiums
A major North American sports league needed player-tracking workflows orchestrated across local stadium systems and centralized graphics engines. Expanso coordinated data processing and delivery locally, ensuring every step executed in the correct sequence before graphics rendering.
Zero live graphics outages across the season
Read Full Case StudyOrchestrating Detection Across Millions of Vehicles
A European OEM needed security workflows coordinated across 2.3 M connected vehicles, local processing units, and centralized SOC systems. Expanso orchestrated detection, filtering, and escalation workflows locally, ensuring alerts were processed in order and delivered reliably.
847 daily alerts instead of 12M - 15K vehicles live in 8 weeks
Read Full Case StudyCoordinating Log Processing Before Splunk
A top-25 US regional bank needed log ingestion, filtering, masking, and routing workflows coordinated before data reached Splunk. Expanso orchestrated these steps at the source, guaranteeing execution order and consistent enforcement.
247 log sources live in 9 weeks - 4.1x faster security alert triage
Read Full Case StudyOrchestrating Field-to-Cloud Processing
A forestry company processed 2.7 TB/day of drone imagery across multiple field offices. Cloud-only workflows caused multi-day delays. Expanso orchestrated local processing steps and synchronized results upstream only after completion.
8 field offices live in 6 weeks - 99.4% of data stays local
Read Full Case StudyWhy Expanso for Data Orchestration
Deploy anywhere
Run orchestration logic in SaaS, on-prem, edge, or hybrid environments
Broad integrations
Coordinate workflows across existing platforms without lock-in or rewrites
Policy-driven orchestration
Rules replace brittle scripts. Execution logic scales without added complexity
Built to scale
Coordinate dozens to thousands of workflows without increasing team size
Frequently Asked Questions
What is a Data Orchestration Platform?
A Data Orchestration Platform coordinates, sequences, and controls data workflows across distributed systems to ensure reliable execution and consistent outcomes.
How is this different from workflow schedulers or DAG tools?
Traditional schedulers operate centrally and assume stable connectivity. Expanso orchestrates workflows where data runs, maintaining execution even during network degradation.
Can Expanso orchestrate across cloud, on-prem, and edge systems?
Yes. Orchestration logic runs across hybrid environments with consistent policy enforcement.
How does Expanso handle failures?
Workflows include built-in buffering, retry, checkpointing, and recovery—without manual intervention.
Does orchestration include governance and security?
Yes. Compliance and policy enforcement are applied during execution, not bolted on afterward.
Start orchestrating your data workflows
Your pipelines already exist. Orchestration determines whether they work together.