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On-prem installers
Sign in| Feature | Etlworks | Workato |
|---|---|---|
| Focus | ETL, ELT, CDC, data sync, data prep, API integration and management, workflow automation, B2B/EDI integration | Business workflow automation, SaaS integration, event-driven recipes, low-code iPaaS |
| Price (Monthly) | $300–$4500+ | $2500–$20000+ |
| Pricing Model | Fixed per tier | Per automation job, connection, and workspace |
| Cost Transparency | High | Low |
| Sources | 260+ | 1000+ SaaS and cloud apps |
| Destinations | Data warehouses, databases, SaaS apps, big data and NoSQL platforms, file storage systems, APIs, message brokers, IoT brokers, email systems | SaaS apps, APIs, and cloud services, limited direct support for databases and warehouses |
| ETL capabilities | ETL, ELT, Reverse ETL, processing by wildcard | Limited ETL inside recipes, no ELT and no purpose-built Reverse ETL |
| Data Replication | Log-based CDC, Full, Incremental | No log-based CDC, basic incremental sync in selected connectors only |
| Data Streaming (queues) | Kafka, Events Hub, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | Kafka and other queues via connectors, primarily for triggering workflows rather than large scale streaming |
| 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 | Basic field mapping and formulas inside recipes, not designed for complex multi-step data transformations |
| Advanced UI capabilities | Grid-based pipeline designer, drag and drop mapping, Explorer for visualizing and querying data | Recipe builder with visual steps and reusable components for business workflows |
| 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 and write JSON in SaaS APIs, limited tooling for flattening and schema management |
| SaaS/PaaS | |
|
| On-premise Deployment | |
|
| On-premise Data Access | |
Limited, through agents and VPN, focused mainly on connecting to SaaS |
| Scalability and Performance | Horizontal scaling and vertical scaling, Supports High Availability (HA), Handles Large Datasets | Scales well for SaaS workflow automation, not designed for high volume batch ETL or heavy analytical workloads |
| Embeddable | |
|
| Data Governance | Automated schema management, access control and encryption, metadata management and data lineage not supported | Audit and access control inside the platform, no dedicated data catalog or lineage for analytical datasets |
| Data Quality Management | Data validation, data cleansing, filtering, deduplication, normalization, and enrichment, automatic schema evolution | Basic validation and checks at recipe step level, no full data quality toolkit |
| Compliance | HIPAA, GDPR, DPA, SOC 2 Type II | SOC 2 and other standard SaaS security controls, varies by edition |
| Collaboration and Dev tools | RBAC, Multi-Tenancy, Version Control, Export and Import, Artifact Patching, Open API, AI Assistant | RBAC, shared workspaces, reuse of recipes and components, limited dev tooling compared to full integration platforms |
| Skill level | Low to Intermediate | Low, optimized for business and operations users |
| Purchase Process | Self-Service (free trial converts to paid self-service), Conversations with Sales is optional | Sales-led process with custom packaging and pricing |
| Vendor lock-in | Monthly and Annual billing, no formal contract required | Annual contracts and tiered plans common, harder to experiment or switch |
Etlworks vs. Workato
Data Integration Platform vs. Business Automation Hub
Side-by-side comparison
Two Strong Platforms, Built for Different Types of Work
Etlworks and Workato both connect systems and automate workflows, but they are designed for different problems. Workato focuses on low-code SaaS automation and business workflows. Etlworks is built for end-to-end data integration, ETL, CDC, streaming, and hybrid deployments. If your main need is orchestrating business actions between applications, Workato can fit. If you need to move, transform, and govern data at scale, Etlworks gives you far more depth with lower long-term cost.
Difference
Why Etlworks Stands Out
Built for Data Pipelines, Not Only App Workflows
Workato is excellent for automating business workflows between SaaS applications, but it is not a full ETL platform. Etlworks is designed for databases, warehouses, files, APIs, queues, IoT, and EDI, so you can centralize both application automation and serious data movement in one place.
Stronger ETL, CDC, and Streaming Capabilities
Etlworks includes native ETL, ELT, Reverse ETL, log-based CDC, wildcard file processing, and streaming support for Kafka, Kinesis, SQS, PubSub, and more. Workato recipes can move records between systems, but they are not a replacement for robust data pipelines and real-time replication.
Hybrid and On-Premise Friendly
Etlworks runs in the cloud, on-premise, or in hybrid environments, and securely connects to on-premise systems without forcing your data into a single cloud provider. Workato is primarily a SaaS automation hub, which can make complex hybrid and on-premise scenarios harder and more expensive to implement.
Predictable Pricing for Growing Workloads
Workato pricing often depends on the number of automations, connections, and workspaces, so costs can rise quickly as usage grows. Etlworks uses transparent, fixed tiers that are easier to forecast and align with how teams actually scale their data and integration workloads.
Choose the Right Platform for Data and Automation
Workato is a strong choice for business automation and SaaS workflows. If you also need serious ETL, CDC, streaming, EDI, and hybrid integration, Etlworks gives you a broader feature set, simpler pricing, and a platform that scales from small projects to enterprise-wide data pipelines. Use Etlworks on its own or alongside tools like Workato when you outgrow recipe-based automation.