How often ChatGPT mentions AWS Glue for etl tools, and how it stacks up against the tools that dominate the answers.
Share of ChatGPT answers naming each tool, same 1 questions.
| # | Tool | Visibility | |
|---|---|---|---|
| 1 | dbt | 100% | |
| 2 | ELT | 100% | |
| 3 | Matillion | 100% | |
| 4 | Airbyte | 100% | |
| 5 | Fivetran | 100% | |
| 6 | AWS Glue ← this tool | 96% | |
| 7 | Informatica | 96% | |
| 8 | Databricks | 87% | |
| 9 | Azure Data Factory | 83% | |
| 10 | Talend | 70% | |
| 11 | Apache Airflow | 61% | |
| 12 | Dagster | 61% |
Free account, see every engine, the trend over time, and which sources to win.
The questions where ChatGPT currently names AWS Glue.
If you mean data engineering ETL/ELT tools, the best choice depends heavily on your stack and whether you want managed or open-source. The 2026 landscape increasingly separates ingestion, transformation, and orchestration rather than relying on one all-in-one ETL product. www.fivetran.compipecode.ai
| Tool | Best for | Main strength | Main drawback |
|---|---|---|---|
| Fivetran | Managed SaaS → warehouse | Very low maintenance, mature connectors | Can get expensive at scale |
| Airbyte | Flexible/open-source ingestion | Large connector ecosystem, self-hosting | More operational work if self-hosted |
| dbt | SQL transformations | Excellent warehouse-native transformation | Not primarily an ingestion tool |
| Matillion | Visual cloud ETL/ELT | GUI + cloud warehouse integration | Cost/complexity at larger scale |
| AWS Glue | AWS environments | Serverless, deep AWS integration | Steeper learning curve |
| Azure Data Factory | Microsoft/Azure shops | Strong Azure ecosystem | Less elegant outside Azure |
| Informatica | Large enterprises | Governance, complex integrations | Expensive/heavyweight |
| Apache Airflow | Pipeline orchestration | Extremely flexible and extensible | You have to build/manage much of the pipeline |
| Talend/Qlik | Enterprise integration | Broad data integration & governance | Enterprise-oriented complexity |
Current 2026 comparisons consistently put Fivetran, Airbyte, Matillion, AWS Glue, Azure Data Factory, Informatica, Talend, and Airflow among the major options. www.integrate.io
One important distinction: Airflow and dbt aren't direct replacements for Fivetran. A modern stack might look like Fivetran/Airbyte → Snowflake/BigQuery → dbt → Airflow, with each component doing a different job. www.fivetran.compipecode.ai
If you tell me your source systems + target (e.g. Salesforce → Snowflake, SQL Server → Databricks, APIs → BigQuery) and approximate data volume, I can narrow this down to the 2–3 best choices.