Directory Data & AnalyticsData Integration & ETLRivery

Rivery

About Rivery

Rivery provides a platform for building ELT data pipelines. The platform supports no-code or custom code pipeline building for analytics or AI. It covers ingestion, transformation, orchestration, activation, and data operations. The product is now offered as Boomi Data Integration, formerly named Rivery. It delivers data to analytics tools, AI models, and intelligent agents.

Used for

Extracting data from apps or databases and loading it into a data lake or warehouse
Transforming raw data into business data models using SQL or Python
Managing dependencies between pipelines with conditional logic, containers, and loops
Pushing data into CRM, Slack, or Tableau using reverse ETL
Migrating data from operational databases to a cloud data warehouse

Who it is for

Small data teams needing core functionality.
Data teams with larger data replication needs.
Enterprises with extensive data and security requirements.

From Rivery's own website, read 2026-10-24. How we build listings.

How to evaluate Data Integration & ETL

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Rivery. It comes from our Data Integration & ETL/ELT buyer guide.

25%

Connector Breadth & Reliability

Coverage of your actual sources (SaaS apps, databases, files, events), depth of each connector (full vs. partial schemas, history), automated schema-drift handling, custom-connector SDK, and who maintains connectors when an upstream API changes

20%

Transformation Model & Engineering Workflow

ELT (in-warehouse SQL/dbt) vs. ETL (engine-side) vs. visual push-down; version control, testing, CI/CD, and lineage; reusability and modularity of models; and fit with your team’s SQL-vs-Python-vs-low-code balance

20%

Real-Time, CDC & Streaming

Log-based change-data-capture, achievable freshness, replication from operational databases, incremental-load handling, schema-evolution on streams, exactly-once semantics, and reverse-ETL/activation back to operational systems

15%

Governance, Lineage & Data Quality

Column-level lineage across the pipeline, in-line data-quality and validation, catalog/metadata integration, masking and PII handling, audit trails, and master-data or data-contract support for regulated environments

10%

Deployment, Security & Sovereignty

SaaS vs. self-hosted vs. hybrid/customer-VPC, where data and credentials reside, SOC 2 / ISO 27001 / HIPAA posture, private networking and BYO-cloud options, RBAC/SSO, and open-source vs. proprietary lock-in

10%

Cost Model & Predictability

Pricing unit (rows/MAR, capacity, credits, compute-hours, per-connector, per-seat), how cost behaves as volume and source count grow, warehouse-compute cost the tool pushes onto you, and whether spend is forecastable against your data growth

Other Data Integration & ETL Vendors

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