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On-prem installers
Sign in| Feature | Etlworks | Zapier |
|---|---|---|
| Focus | ETL, ELT, CDC, data sync, data prep, API integration and management, workflow automation, B2B/EDI integration | No-code app automation, simple event-driven workflows, personal and team productivity |
| Price (Monthly) | $300–$4500+ | $20–$200+ depending on tasks and users |
| Pricing Model | Fixed per tier | Task-based and tiered usage plans |
| Cost Transparency | High | Low to Moderate, costs vary based on task volume |
| Sources | 260+ | 5000+ SaaS and web applications |
| Destinations | Data warehouses, databases, SaaS apps, big data and NoSQL platforms, file storage systems, APIs, message brokers, IoT brokers, email systems | SaaS apps and APIs, limited direct support for databases and warehouses, no native big data targets |
| ETL capabilities | ETL, ELT, Reverse ETL, processing by wildcard | No ETL engine, record level field mapping only inside zaps |
| Data Replication | Log-based CDC, Full, Incremental | No CDC, no bulk replication, basic polling in some connectors |
| Data Streaming (queues) | Kafka, Events Hub, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | No native queue integration for streaming workloads |
| 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 | Simple field mapping, formatting rules, and filters inside zaps, not suitable for complex multi step transformations |
| Advanced UI capabilities | Grid-based pipeline designer, drag and drop mapping, Explorer for visualizing and querying data | Zap builder with triggers and actions, optimized for small workflows rather than full pipelines |
| 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 | JSON payloads from APIs, basic field extraction, no schema management or flattening tools |
| SaaS/PaaS | |
|
| On-premise Deployment | |
|
| On-premise Data Access | |
Possible via webhooks or custom integrations, not a core strength |
| Scalability and Performance | Horizontal scaling and vertical scaling, Supports High Availability (HA), Handles Large Datasets | Designed for low to medium volume workflows, not for large batch loads or high volume streaming |
| Embeddable | |
|
| Data Governance | Automated schema management, access control and encryption, metadata management and data lineage not supported | Basic audit logs and permissions inside the product, no dedicated data governance or lineage features |
| Data Quality Management | Data validation, data cleansing, filtering, deduplication, normalization, and enrichment, automatic schema evolution | Limited to simple conditions and filters inside each zap step |
| Compliance | HIPAA, GDPR, DPA, SOC 2 Type II | Standard SaaS security and compliance posture, varies by plan and region |
| Collaboration and Dev tools | RBAC, Multi-Tenancy, Version Control, Export and Import, Artifact Patching, Open API, AI Assistant | Shared folders, simple permissions, and version history for zaps, limited developer tooling |
| Skill level | Low to Intermediate | Low, targeted at non technical business users |
| Purchase Process | Self-Service (free trial converts to paid self-service), Conversations with Sales is optional | Self service signup with online plans, sales involvement for larger teams |
| Vendor lock-in | Monthly and Annual billing, no formal contract required | Monthly and Annual plans, workflows tightly tied to Zapier zap model |
Etlworks vs. Zapier
Data Integration Platform vs. No-code App Automation
Side-by-side comparison
Automation for Simple Tasks vs. Integration for Serious Data Work
Etlworks and Zapier both connect applications, but they serve different needs. Zapier focuses on lightweight, event-driven app automation for individual teams and small workflows. Etlworks is built for full data pipelines, ETL, CDC, streaming, EDI, and hybrid integration across databases, warehouses, files, APIs, and queues. If you just need to sync a few records between tools, Zapier can be enough. If you are building reliable data infrastructure that scales, Etlworks is a better fit.
Difference
Why Etlworks Stands Out
From Simple App Triggers to Full Data Pipelines
Zapier is great for simple triggers like "when a form is submitted, create a record in CRM". Etlworks covers those use cases and also handles full pipelines between databases, warehouses, lakes, files, APIs, queues, and EDI systems, so you do not have to piece together fragile chains of zaps for serious data work.
Real ETL, CDC, and Streaming Capabilities
Etlworks includes native ETL and ELT, Reverse ETL, log based CDC, streaming to and from Kafka, Kinesis, SQS, PubSub, and more. Zapier moves individual records through workflows but does not offer a dedicated ETL engine, bulk replication, or real time change capture for analytical systems.
Better Fit for Analytics, Reporting, and Data Platforms
If your goal is to populate a warehouse, lake, or BI platform, Etlworks provides the connectors, transformations, and scheduling you need. Zapier is focused on operational app to app automation, which can be helpful at the edge but is not designed to be the backbone of your analytics stack.
Predictable Pricing as Workloads Grow
Zapier pricing is tied to task counts and usage, which can become unpredictable as automations grow. Etlworks uses clear, fixed tiers for integration workloads, so teams can scale data volumes and pipelines without constantly watching task consumption or changing plans.
Use Zapier Where It Fits, Use Etlworks Where It Matters
Zapier is a solid option for quick wins and lightweight automation between SaaS tools. When you need reliable data pipelines, CDC, streaming, EDI, or hybrid integrations that connect your operational systems with your analytics stack, Etlworks is the better choice. Many teams use both, with Zapier for simple productivity flows and Etlworks for core data integration and reporting.