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Sign in| Feature | Etlworks | Azure Data Factory |
|---|---|---|
| Focus | ETL, ELT, CDC, data sync, data prep, API integration and management, workflow automation, B2B/EDI integration | Data sync, workflow automation |
| Price (Monthly) | $300–$4500+ | $500–$8000+ |
| Pricing Model | Fixed per tier | Consumption-based |
| Cost Transparency | High | Moderate |
| Sources | 260+ | 100+ |
| Destinations | Data warehouses, databases, SaaS apps, big data and NoSQL platforms, file storage systems, APIs, message brokers, IoT brokers, email systems | Data warehouses, databases, SaaS apps |
| ETL capabilities | ETL, ELT, Reverse ETL, processing by wildcard | ETL, ELT, Reverse ETL |
| Data Replication | Log-based CDC, Full, Incremental | Log-based CDC, Full, Incremental |
| Data Streaming (queues) | Kafka, Events Hub, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | Kafka, EventHubs, ServiceBus |
| Data Streaming (IoT brokers) | MQTT brokers |  |
| Transformations | Drag-and-drop transformations, cleaning, normalization, restructuring, SQL/JavaScript/Python/XLS/Shell scripting, metadata-driven interactive mapping, lookups, enrichment, soft deletes | Cleansing, normalization, enrichment, code-free transformations, code-based transformations, interactive mapping |
| Advanced UI capabilities | Grid-based pipeline designer, drag and drop mapping, Explorer for visualizing and querying data | Canvas-based drag-and-drop pipeline designer, drag and drop mapping, drag and drop transformations, formula builder |
| API Management |  |
|
| API Integration | |
|
| EDI Processing | Read and write X12, EDIFACT, HL7, FHIR, NCPD and VDA messages | |
| Nested Document Processing | Read, write, normalize and flatten: JSON, XML, Avro, Parquet | Read, write and flatten: JSON, XML, Avro, Parquet |
| SaaS/PaaS | |
|
| On-premise Deployment | |
|
| On-premise Data Access | |
|
| Scalability and Performance | Horizontal scaling and vertical scaling, Supports High Availability (HA), Handles Large Datasets | Automatic scaling with cloud infrastructure, Supports High Availability (HA), Handles Large Datasets |
| Embeddable | |
|
| Data Governance | Automated schema management, access control and encryption, metadata management and data lineage not supported | Metadata management and data lineage through integration with Azure Purview |
| Data Quality Management | Data validation, data cleansing, filtering, deduplication, normalization, and enrichment, automatic schema evolution | Supports data quality through integration with Azure Purview for profiling, validation, and cleansing |
| Compliance | HIPAA, GDPR, DPA, SOC 2 Type II | GDPR, HIPAA, SOC 2 compliant; leverages Azure compliance framework |
| Collaboration and Dev tools | RBAC, Multi-Tenancy, Version Control, Export and Import, Artifact Patching, Open API, AI Assistant | RBAC via Azure IAM, Multi-Tenancy, Integration with Azure DevOps, Open API, Export and Import, AI Assistant |
| Skill level | Low to Intermediate | Low to Intermediate |
| Purchase Process | Self-Service (free trial converts to paid self-service), Conversations with Sales is optional | Self-Service (with free trial via $200 credit for 30 days, converts to paid self-service) |
| Vendor lock-in | Monthly and Annual billing, no formal contract required | Monthly billing, no formal contract required |
Etlworks vs. Azure Data Factory
Modern Data Integration — Without Azure-Only Limits
Side-by-side comparison
Optimized for Azure, or Optimized for Everything?
Both Etlworks and Azure Data Factory offer strong capabilities for moving and transforming data. ADF is a great choice for organizations deeply embedded in the Azure ecosystem, offering seamless integrations with services like Azure Purview and Fabric. Etlworks, however, is a complete, cloud-agnostic integration platform — delivering broader functionality, hybrid deployments, and predictable pricing without cloud lock-in.
Difference
Why Etlworks Stands Out
True Platform Independence
Azure Data Factory is tightly coupled with Azure services, making it a natural fit for organizations fully invested in the Azure ecosystem. Etlworks works across clouds, on-premises, and hybrid environments — giving you the freedom to integrate and orchestrate data wherever it lives, without vendor lock-in.
Broader Integration Capabilities
While ADF focuses primarily on data movement and orchestration, Etlworks offers a complete integration platform — including ETL, ELT, reverse ETL, CDC, real-time streaming, API management, B2B/EDI processing, and complex multi-source transformations.
Predictable Pricing and Lower Barrier to Entry
Azure Data Factory’s consumption-based pricing can vary widely depending on usage patterns, leading to unpredictable costs over time. Etlworks offers fixed, transparent pricing starting at $300 per month — making it easier to budget and scale without surprise charges.
Deployment Flexibility and Broader Connector Support
Etlworks supports over 260 connectors — including databases, SaaS apps, message brokers, and IoT platforms — and can operate across cloud and on-premise environments. ADF primarily supports Azure-connected systems and cloud deployments, limiting flexibility for hybrid or multi-cloud strategies.
Full-Scale Data Integration, Without Cloud Lock-In
Azure Data Factory excels for Azure-native projects, but Etlworks provides the flexibility, breadth, and cost transparency needed for today’s hybrid, multi-cloud, and on-premise environments. If you’re looking for more than just data movement — and want true integration, flexibility, and control — Etlworks is the smart choice.