A Quick Look

Capabilities

Ascend

dbt

Pipeline Coverage

Ingest → Transform → Deliver in one platform

Cost Efficiency

Auto-optimized execution reduces compute waste

Inefficient runs = higher cloud compute bills

Automation

Event-driven, rule-based automation built in

Manual triggers or external workflows

Orchestration

Native orchestration—no external scheduler needed

No built-in orchestration across jobs

Performance Optimization

Smart Tables minimize reprocessing and cost

Full reprocessing common—tune jobs manually

Scalability

Scales cleanly without manual overhead

Scaling requires more jobs, more effort

Observability

Real-time lineage, logs, and health monitoring

Limited pipeline visibility and error insights

Developer Flexibility

Full-code, low-code, and AI-native tooling

UI-first; flexibility drops at scale

Where Matillion Falls Short

Matillion makes it easy to build pipelines—but not necessarily to scale them. As data volumes grow and complexity kicks in, teams start to feel the friction.

Full reprocessing burns time and compute

Matillion doesn't optimize for change—pipelines often re-run everything, even when nothing’s changed. That means longer runtimes and bigger cloud bills.

No built-in orchestration or automation

You’re writing scripts, scheduling jobs, and hoping dependencies line up. Want dynamic, event-driven workflows? Look elsewhere.

Performance tuning = trial and error

Want to debug pipeline slowdowns? Get ready to sift through logs and guess where time and money are leaking.

Scaling = scaling your maintenance overhead

As you add more pipelines, environments, and team members, complexity increases fast—and Matillion doesn’t offer the observability or guardrails to keep things stable.

Hard to break out of the UI

While the drag-and-drop editor is great at first, it becomes limiting as you want more flexibility, modularity, or integration with dev workflows.

Included in Every Plan

Every Ascend plan includes full access to the platform — no feature gating, no user limits. Build, automate, and scale with confidence using the entire suite of AI-powered tools.

Data Ingestion

Say goodbye to fragile handoffs and brittle ingest jobs.

Whether you’re moving data from lakes, warehouses, databases, APIs, or legacy systems, Ascend makes it easy. Flexible connectors and dynamic schema handling ensure your pipelines stay reliable as systems evolve.

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Transformation

Transform Data with Speed at Scale

Ascend automates orchestration using rich metadata and event-driven triggers—so pipelines run only when needed, and custom logic is easy to build in.

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Orchestration

Orchestration That Writes Itself

Monitor pipeline performance, trace lineage end-to-end, and debug faster with real-time, metadata-powered insights.

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Observability

See Everything. Fix Anything.

Run faster, spend less—Ascend uses metadata and fingerprinting to cut unnecessary compute without sacrificing performance.

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DataOps

Built-In DataOps for Modern Teams

From Git-backed workflows to access controls and secure deployment environments, Ascend simplifies operational excellence with native support for modern DevOps practices.

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Say Goodbye to Fragile Handoffs and Brittle Ingest Jobs

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Transform Data
with Speed at Scale

From SQL to Python, declarative to imperative, Ascend supports multiple authoring modes — all integrated with version control and modular pipeline design. Build fast, iterate safely.

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Orchestration
that Writes Itself

Ascend’s DataAware engine lets you design intelligent workflows using the metadata you already have — turning your designs into powerful automation. Ascend's Smart Tables process data up to 100x faster.

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See Everything.
Fix Anything.

From real-time monitoring to full lineage and change tracking, Ascend gives you deep visibility into your data flows — so you can spot issues fast and optimize with confidence.

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Built-In DataOps
for Modern Teams

From Git-backed workflows to access controls and secure deployment environments, Ascend simplifies operational excellence with native support for modern DataOps best practices.

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Intelligence at the Core

Ascend's Intelligence Core combines metadata, automation, and AI in a layered architecture that empowers teams to build pipelines 7x faster and cut processing costs by 83%.

Ascend UI - Data Pipeline Deployment Dashboard

Unified Metadata Collection

Ascend tracks data, code, and user actions in a unified metadata layer — powering automation, observability, and auditability through the entire data lifecycle.

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DataAware™ Automation Engine

Ascend’s automation engine uses rich metadata to orchestrate pipelines — managing dependencies, triggering tasks, and supporting custom event-driven workflows.

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Ascend Agentic Engineering experience in the UI

Integrated AI Agents

Let AI do the tedious parts of data engineering — Ascend’s context-aware agents suggest code, explain logic, generate docs, and even automate steps on your behalf.

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