Ingestr
Open SourceAbout Ingestr
Ingestr is a command-line app that copies data from any source into any destination using command-line flags, without code. It loads incrementally with append, merge or delete+insert.
Used for
- Copying data from a database into a destination.
From Ingestr's own website, read 2026-10-23. 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 Ingestr. 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
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Quick Facts
bruin-data.github.io/ingestrCategoryData & Analytics
SubcategoryData Integration & ETL
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