Comparison
Palantir Foundry is an end-to-end operational data platform with deep ontology and analytics. Etlworks delivers focused data integration — ETL/ELT, CDC, APIs, EDI — at predictable pricing without the engagement model.
The verdict
Feature breakdown
| Capability | Etlworks | Palantir Foundry |
|---|---|---|
| Pricing & commercial | ||
| Starting price (monthly) | $300 | Contact sales (enterprise engagement) |
| Pricing model | Fixed per tier | Annual platform contracts |
| Integration scope | ||
| Sources | 260+ | Broad (custom) |
| ETL capabilities | ETL, ELT, Reverse ETL, wildcard processing | Full ETL/ELT + ontology |
| API management | Full | Within ontology |
| On-prem deployment | Apollo | |
| Transformations | ||
| Visual mapping | drag-and-drop designer with live preview | Pipeline Builder |
| Scripting languages | SQL, JavaScript, Python, XSLT, shell | Python, SQL, Java |
| Nested and hierarchical data | JSON, XML, Avro, Parquet — read, write, normalize, flatten by dragging | JSON and XML, varying depth |
| Warehouse pushdown (ELT) | transform before load or in the warehouse, same engine | |
| Reusable logic | macros, templates, and 3,900+ prebuilt flow templates | reusable components and templates |
| Lookups and enrichment | Lookup Builder for cross-source lookups | lookup components |
| Data validation | validation rules with per-step error handling | validation and cleansing components |
| Orchestration & workflow | ||
| Scheduling | Cron expressions and fixed intervals, with per-schedule parameters | Build schedules on datasets |
| Event-driven triggers | HTTP listeners and webhooks, message queues, file and email events | dataset-change triggers |
| Continuous execution | looping schedules for CDC and queue consumers | long-running listeners and services |
| Visual workflow builder | Composer canvas, 200+ flow types | visual process designer |
| Nested workflows | nested flows with conditional and looped steps | pipeline dependency graph |
| Run external tools | shell and SSH scripts, CLI, JavaScript, Python, SQL, HTTP calls | Partial — code repositories and transforms |
| Parallel execution | overlapping schedules run as independent, separately cancellable instances | parallel branches |
| Retries and error handling | per-step exception handling with notifications | retry, error handlers, dead letter |
| Run monitoring | per-schedule status, run history, automatic Flow Findings reports | process dashboards and alerts |
| CDC & Streaming | ||
| CDC engine | Debezium-compatible, built-in (no Kafka required) | Streaming pipelines (Foundry Streaming) |
| Database CDC sources | MySQL, Postgres, SQL Server, Oracle, MongoDB, DB2, others | Connector-based |
| Streaming queues | Kafka, EventHubs, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | Kafka |
| IoT brokers | MQTT brokers | |
| Real-time replication | Log-based CDC, full, incremental | Streaming pipelines |
| Change tracking modes | Log-based, trigger-based, timestamp/high-watermark | Log-based, time-based |
| Developer experience | ||
| REST API | full API for flows, connections, schedules, and runs | |
| CLI | full CLI with built-in SQL | |
| MCP server | built-in — connect Cursor, Claude, or ChatGPT to your instance | |
| Client libraries | Python, Bash, and PowerShell clients | Partial — vendor SDKs |
| Version control | built-in — automatic history, diff, and revert on every artifact | branching and code repositories |
| Embeddable / white-label | Partial — OEM agreements | |
| Compliance & security | ||
| SOC 2 Type 2 | audited; report under NDA, SOC 3 public | |
| HIPAA | supported with a BAA | enterprise agreements |
| GDPR / DPA | compliant, DPA available | |
| SSO and MFA | SAML SSO, optional 2FA, JWT stateless auth | SAML and directory integration |
| Role and artifact-level access | six roles plus tag-based scoping of flows, connections, and schedules | role and project-level access |
| Encryption and data handling | TLS in transit, encrypted at rest, customer-managed PGP, SSH tunnels, IP allowlisting; rows are not persisted by default | encrypted in transit and at rest |
| Audit logging | admin actions logged, access logs monitored | |
| Security testing | monthly vulnerability and penetration scans, static analysis blocking every build, periodic third-party audits | vendor-managed |
| Gen AI | ||
| AI agent | Built-in agent (Simba) — builds and edits flows from chat | AIP — Artificial Intelligence Platform |
| Agent capabilities | Reads metadata, reads/samples data, writes JS & SQL, schedules, deploys, monitors | Operational agents, ontology-driven LLM workflows, decision automation |
| 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 | full operational analytics platform |
| Chat across product | Same agent context on every screen | |
| CLI for agent | Full CLI access for run/deploy/monitor/manage | |
| Trains on customer data | Never | Per Palantir enterprise terms |