Comparison
Both move data into cloud warehouses. Etlworks goes further — full ETL, CDC, API integration, EDI, and on-prem deployment, with fixed pricing instead of consumption-based.
The verdict
Feature breakdown
| Capability | Etlworks | Fivetran |
|---|---|---|
| Pricing & commercial | ||
| Starting price (monthly) | $300 | $1,000+ |
| Pricing model | Fixed per tier | Consumption-based (per-row) |
| Cost transparency | High — flat rate | Low — varies with data volume |
| Vendor lock-in | Monthly or annual, no contract | Annual, no contract |
| Integration scope | ||
| Sources | 260+ | 700+ |
| Destinations | Warehouses, databases, SaaS, NoSQL, files, APIs, queues, IoT, email | Data warehouses, data lakes |
| ETL capabilities | ETL, ELT, Reverse ETL, wildcard processing | ELT, limited ETL |
| API management | Full | |
| EDI processing | X12, EDIFACT, HL7, FHIR | |
| On-prem deployment | ||
| Embeddable | ||
| CDC & Streaming | ||
| CDC engine | Debezium-compatible, built-in (no Kafka required) | Native managed CDC |
| Database CDC sources | MySQL, Postgres, SQL Server, Oracle, MongoDB, DB2, others | MySQL, Postgres, SQL Server, Oracle, MongoDB, DB2, others |
| Streaming queues | Kafka, EventHubs, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | Kafka |
| IoT brokers | MQTT brokers | |
| Real-time replication | Log-based CDC, full, incremental | Log-based CDC, full, incremental |
| Change tracking modes | Log-based, trigger-based, timestamp/high-watermark | Log-based |
| Gen AI | ||
| AI agent | Built-in agent (Simba) — builds and edits flows from chat | Partial — MCP-based agents for connector creation (developer-focused) |
| Agent capabilities | Reads metadata, reads/samples data, writes JS & SQL, schedules, deploys, monitors | Generate connectors from API docs, debug sync failures |
| Natural-language flow building | ‘Vibe-build’ — create flows by describing what you want | Partial — primarily for connector authoring |
| AI-driven mapping | Auto-suggests source-to-destination mappings | |
| Built-in analytics | Agent runs analysis on flow data and pipeline behavior | |
| Chat across product | Same agent context on every screen | |
| CLI for agent | Full CLI access for run/deploy/monitor/manage | Partial — via MCP infrastructure |
| Trains on customer data | Never | Not by default |
| Transformations | ||
| Drag-and-drop | Full visual designer | Limited |
| Scripting languages | SQL, JavaScript, Python, XLS, Shell | SQL, dbt |
| Nested document handling | JSON, XML, Avro, Parquet — read, write, normalize, flatten | JSON, XML — read, write, normalize |
| Compliance & security | ||
| SOC 2 Type II | ||
| HIPAA | ||
| GDPR / DPA | ||
| PCI DSS / ISO 27001 | PCI DSS L1, ISO 27001 | |
| Data lineage tracking | Partial — schema management, RBAC, encryption | Full lineage, column blocking, hashing |