Comparison
DMS is a database migration service that plenty of teams leave running as a pipeline. It replicates tables well and does nothing else. Etlworks gives you the same log-based CDC plus transformations, orchestration, APIs, and EDI, on any cloud or on-prem.
The verdict
Feature breakdown
| Capability | Etlworks | AWS DMS |
|---|---|---|
| Pricing & commercial | ||
| Starting price (monthly) | $300 | Serverless from about $0.082 per DCU-hour, plus CDC log storage |
| Pricing model | Fixed per tier | Consumption — DCU or instance hours, storage, and egress |
| Cost transparency | High — flat rate | Medium — cheap to start, long-running CDC tasks accumulate storage |
| Vendor lock-in | Monthly or annual, no contract | AWS-native, no contract |
| Ownership | Independent, founder-run | Amazon Web Services |
| Integration scope | ||
| Sources | 260+ | Databases only — Oracle, SQL Server, PostgreSQL, MySQL, MongoDB, Db2, SAP ASE, S3 |
| Destinations | Warehouses, databases, SaaS, NoSQL, files, APIs, queues, IoT, email | AWS databases, Redshift, S3, Kinesis, OpenSearch, Kafka |
| ETL capabilities | ETL, ELT, Reverse ETL, wildcard processing | table mappings and filters, not transformations |
| API management | Full | |
| EDI processing | X12, EDIFACT, HL7, FHIR | |
| On-prem deployment | AWS-hosted; reaches on-prem sources over VPN or Direct Connect | |
| Embeddable | ||
| Transformations | ||
| Visual mapping | drag-and-drop designer with live preview | Partial — table mappings and column filters |
| Scripting languages | SQL, JavaScript, Python, XSLT, shell | JSON transformation rules only |
| Nested and hierarchical data | JSON, XML, Avro, Parquet — read, write, normalize, flatten by dragging | Partial — passes JSON through, unpacking happens downstream |
| Warehouse pushdown (ELT) | transform before load or in the warehouse, same engine | Partial — load raw, transform with another tool |
| Reusable logic | macros, templates, and 3,900+ prebuilt flow templates | |
| Lookups and enrichment | Lookup Builder for cross-source lookups | |
| Data validation | validation rules with per-step error handling | |
| Orchestration & workflow | ||
| Scheduling | Cron expressions and fixed intervals, with per-schedule parameters | Task start and stop, no job scheduler |
| Event-driven triggers | HTTP listeners and webhooks, message queues, file and email events | |
| Continuous execution | looping schedules for CDC and queue consumers | replication runs continuously |
| Visual workflow builder | Composer canvas, 200+ flow types | |
| Nested workflows | nested flows with conditional and looped steps | |
| Run external tools | shell and SSH scripts, CLI, JavaScript, Python, SQL, HTTP calls | orchestrate with Step Functions or EventBridge |
| Parallel execution | overlapping schedules run as independent, separately cancellable instances | parallel apply and multiple tasks |
| Retries and error handling | per-step exception handling with notifications | Partial — task restart, recovery from the log position |
| Run monitoring | per-schedule status, run history, automatic Flow Findings reports | task status and lag metrics |
| CDC & Streaming | ||
| CDC engine | Debezium-compatible, built-in (no Kafka required) | log-based CDC, built for migration cutover |
| Database CDC sources | MySQL, Postgres, SQL Server, Oracle, MongoDB, DB2, others | Oracle, SQL Server, PostgreSQL, MySQL, MongoDB, Db2, SAP ASE |
| Streaming queues | Kafka, EventHubs, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | Kinesis and MSK, as targets only |
| IoT brokers | MQTT brokers | |
| Real-time replication | Log-based CDC, full, incremental | ongoing replication after full load |
| Change tracking modes | Log-based, trigger-based, timestamp/high-watermark | Log-based, full load plus CDC |
| Developer experience | ||
| REST API | full API for flows, connections, schedules, and runs | cloud API |
| CLI | full CLI with built-in SQL | cloud CLI |
| MCP server | built-in — connect Cursor, Claude, or ChatGPT to your instance | |
| Client libraries | Python, Bash, and PowerShell clients | cloud SDKs in many languages |
| Version control | built-in — automatic history, diff, and revert on every artifact | Partial — infrastructure-as-code, not artifact history |
| Embeddable / white-label | ||
| Compliance & security | ||
| SOC 2 Type 2 | audited; report under NDA, SOC 3 public | plus ISO 27001, PCI, FedRAMP |
| HIPAA | supported with a BAA | covered by the cloud BAA |
| GDPR / DPA | compliant, DPA available | |
| SSO and MFA | SAML SSO, optional 2FA, JWT stateless auth | cloud IAM and directory integration |
| Role and artifact-level access | six roles plus tag-based scoping of flows, connections, and schedules | fine-grained IAM policies |
| Encryption and data handling | TLS in transit, encrypted at rest, customer-managed PGP, SSH tunnels, IP allowlisting; rows are not persisted by default | platform KMS, customer-managed keys |
| Audit logging | admin actions logged, access logs monitored | cloud-native audit trail |
| Security testing | monthly vulnerability and penetration scans, static analysis blocking every build, periodic third-party audits | continuous, platform-wide |
| Gen AI | ||
| AI agent | Built-in agent (Simba) — builds and edits flows from chat | |
| Agent capabilities | Reads metadata, reads/samples data, writes JS & SQL, schedules, deploys, monitors | |
| Natural-language flow building | ‘Vibe-build’ — create flows by describing what you want | |
| 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 | Partial — Amazon Q across the AWS console, not DMS-specific |
| CLI for agent | Full CLI access for run/deploy/monitor/manage | AWS CLI, not agent-driven |
| Trains on customer data | Never | Per AWS terms |