Comparing AWS Glue with Census and Weld
Carolina Russ6 min read
What is AWS Glue
AWS Glue is a fully managed, serverless ETL service provided by Amazon Web Services. It automatically discovers and catalogs metadata (Glue Data Catalog), generates ETL code in PySpark, and runs jobs on demand or schedules them. Glue integrates natively with AWS data stores (S3, Redshift, RDS, DynamoDB) and third-party sources via JDBC.
Pros
- Serverless—no infrastructure to manage; Glue provisions compute as needed (Apache Spark under the hood).
- Built-in Data Catalog for schema discovery, versioning, and integration with Athena and Redshift Spectrum.
- Supports Python (PySpark) and Scala ETL scripts with mapping and transformation APIs for complex logic.
- Deep integration with AWS ecosystem (CloudWatch monitoring, IAM for security, S3 triggers).
Cons
- Cost can be unpredictable for long-running or high-concurrency jobs (billed per Data Processing Unit-hour).
- Debugging PySpark jobs in Glue requires jumping between AWS console logs and code; local testing is limited compared to local Spark.
- On-premises or multi-cloud data sources require additional setup (Glue has JDBC connectors but network config can be complex).
AWS Glue Documentation:
What I like about AWS Glue
Glue’s automatic schema discovery and code generation speed up ETL development—once you point it to a data source, it builds tables in the Data Catalog and scaffolds PySpark jobs for you.
What I dislike about AWS Glue
Managing large-scale Glue jobs can be tricky—job concurrency limits and developer debugging in PySpark jobs require more AWS expertise.
What is Census
Census is a leading Reverse ETL platform that syncs data from your data warehouse back into SaaS tools like Salesforce, HubSpot, and Marketo. It integrates deeply with dbt and modern warehouses, enabling no-code mapping, incremental upserts, and reliable syncs to operational systems in near real time.
Pros
- Warehouse-centric: works directly on tables or dbt models
- No-code field mapping with live previews
- Broad destination support: Salesforce, HubSpot, Slack, Google Sheets, etc.
- Incremental upserts ensure data consistency with no duplicates
- Deep dbt integration and “analytics-as-code” workflows (YAML config)
- Flexible scheduling and API triggers for near real-time use cases
Cons
- Focuses only on reverse ETL—requires a separate ELT tool for ingestion
- Pricing based on rows or syncs can be expensive at very large volumes
- Complex transformations must be done upstream in the warehouse/dbt
- Dependent on destination API rate limits, which can slow large syncs
- SaaS-only (no on-prem deployment)
Census Overview (G2):
What I like about Census
Census is the fastest and most reliable reverse ETL platform with 99.5% uptime and premium support for all plans. It delivers transformed data at time-of-use—fueling rapid data activation in operational tools without relying on leaky pipelines.
What I dislike about Census
What is Weld
Weld is a powerful ETL platform that seamlessly integrates ELT, data transformations, reverse ETL, and AI-assisted features into one user-friendly solution. With its intuitive interface, Weld makes it easy for anyone, regardless of technical expertise, to build and manage data workflows. Known for its premium quality connectors, all built in-house, Weld ensures the highest quality and reliability for its users. It is designed to handle large datasets with near real-time data synchronization, making it ideal for modern data teams that require robust and efficient data integration solutions. Weld also leverages AI to automate repetitive tasks, optimize workflows, and enhance data transformation capabilities, ensuring maximum efficiency and productivity. Users can combine data from a wide variety of sources, including marketing platforms, CRMs, e-commerce platforms like Shopify, APIs, databases, Excel, Google Sheets, and more, providing a single source of truth for all their data.
Pros
- Premium quality connectors and reliability
- User-friendly and easy to set up
- AI assistant
- Very competitive and easy-to-understand pricing model
- Reverse ETL option
- Lineage, orchestration, and workflow features
- Advanced transformation and SQL modeling capabilities
- Ability to handle large datasets and near real-time data sync
- Combines data from a wide range of sources for a single source of truth
Cons
- Requires some technical knowledge around data warehousing and SQL
- Limited features for advanced data teams
A reviewer on G2 said:
What I like about Weld
First and foremost, Weld is incredibly user-friendly. The graphical interface is intuitive, which makes it easy to build data workflows quickly and efficiently. Even with little experience in SQL and pipeline management, we found that Weld was straightforward and easy to use. What really impressed me, however, was Weld's flexibility. It was able to handle data from a wide variety of sources, including SQL databases, Google Sheets, and even APIs. The solution also allowed us to customize my data transformations in a way that best suited my needs. Whether I needed to clean data, join tables, or aggregate data, Weld had the necessary tools to accomplish the task. Weld's performance was also exceptional. I was able to run large-scale ETL jobs quickly and efficiently, with minimal downtime via a Snowflake instance and visualization via own-hosted Metabase. The solution's scalability meant that I could process more data without any issues. Another standout feature of Weld was its support. I never felt lost or unsure about how to use a particular feature, as the support team was always quick to respond to any questions or concerns that I had. Overall, I highly recommend Weld as an ETL solution. Its user-friendliness, flexibility, performance, and support make it an excellent choice for anyone looking to streamline their data integration processes. I will definitely be using Weld for all my ETL needs going forward.
What I dislike about Weld
Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.
AWS Glue vs Census: Ease of Use and User Interface
AWS Glue
AWS Glue Studio provides a visual job authoring interface where you can drag-and-drop nodes to transform data, but deeper customizations still require PySpark code. The console UI can be intimidating for new users.
Census
Census provides an intuitive UI for mapping warehouse fields to destination fields, with live previews—non-technical business users quickly adopt it for operational data syncs.
AWS Glue vs Census: Pricing Transparency and Affordability
AWS Glue
Glue charges per Data Processing Unit (DPU)-hour; for example, running a small job for one hour costs ~$0.44 * number of DPUs used. While serverless, large or long-running jobs can become costly if not optimized.
Census
While there’s a free tier to get started, professional plans based on usage can add up for large enterprises. Still, ROI often justifies the investment by automating data activation in CRM/marketing tools.
AWS Glue vs Census: Comprehensive Feature Set
AWS Glue
Features include automated schema discovery (Glue Data Catalog), PySpark/Scala job generation, job scheduling & triggers, DataBrew for visual data prep, and Glue Workflows for orchestration. Also supports streaming ETL via Glue streaming jobs.
Census
Census focuses on reverse ETL: no-code mapping, incremental upserts keyed on primary keys, scheduling, and deep dbt integration. It provides monitoring dashboards, alerting, and a CLI/API for GitOps workflows.
AWS Glue vs Census: Flexibility and Customization
AWS Glue
Glue allows custom PySpark scripts, supports Python libraries via wheel files, and you can integrate with AWS Lambda for custom triggers. However, debugging and local runs can be challenging compared to self-managed Spark.
Census
Mapping logic is as flexible as your SQL—any complex query can feed Census. Users can customize scheduling (cron or event triggers) and configure failure handling. It adapts well but relies on warehouse transformations for complex logic.
Summary of AWS Glue vs Census vs Weld
| Weld | AWS Glue | Census | |
|---|---|---|---|
| Connectors | 200++ | 50+ | 130+ |
| Price | $99 / Unlimited usage | $0.44 per DPUs-hour (development endpoints) + per-job costs | Free tier; Pro ~$350/mo for 2 destinations |
| Free tier | No | Yes | Yes |
| Location | EU | AWS Global (multi-region) | US |
| Extract data (ETL) | Yes | Yes | No |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | Yes |
| Transformations | Yes | Yes | No |
| AI Assistant | Yes | No | No |
| On-Premise | No | No | No |
| Orchestration | Yes | Yes | Yes |
| Lineage | Yes | Yes | No |
| Version control | Yes | No | Yes |
| Load data to and from Excel | Yes | Yes | No |
| Load data to and from Google Sheets | Yes | No | Yes |
| Two-Way Sync | Yes | No | No |
| dbt Core Integration | Yes | Yes | Yes |
| dbt Cloud Integration | Yes | No | No |
| OpenAPI / Developer API | Yes | No | Yes |
| G2 Rating | 4.8 | 4.1 | 4.5 |
Conclusion
You’re comparing AWS Glue, Census, Weld. Each of these tools has its own strengths:
- AWS Glue: features include automated schema discovery (glue data catalog), pyspark/scala job generation, job scheduling & triggers, databrew for visual data prep, and glue workflows for orchestration. also supports streaming etl via glue streaming jobs. . glue charges per data processing unit (dpu)-hour; for example, running a small job for one hour costs ~$0.44 * number of dpus used. while serverless, large or long-running jobs can become costly if not optimized. .
- Census: census focuses on reverse etl: no-code mapping, incremental upserts keyed on primary keys, scheduling, and deep dbt integration. it provides monitoring dashboards, alerting, and a cli/api for gitops workflows.. while there’s a free tier to get started, professional plans based on usage can add up for large enterprises. still, roi often justifies the investment by automating data activation in crm/marketing tools..
- Weld: weld integrates elt, data transformations, and reverse etl all within one platform. it also provides advanced features such as data lineage, orchestration, workflow management, and an ai assistant, which helps in automating repetitive tasks and optimizing workflows.. weld offers a straightforward and competitive pricing model, starting at $99 for 2 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..
