Comparing AWS Glue with Meltano and Weld
Carolina Russ6 min read
What is AWS Glue
AWS Glue is a fully managed, serverless ETL service from AWS that automates data discovery, cataloging, and transformation using the Glue Data Catalog and PySpark. It integrates natively with AWS services like S3, Redshift, RDS, and DynamoDB, and supports third-party sources via JDBC. Glue offers both batch and streaming ETL, along with visual tools like Glue Studio and low-code options like DataBrew. It automatically scales based on workload, supports job scheduling and orchestration, and provides monitoring through CloudWatch. Ideal for AWS-centric teams, Glue simplifies large-scale data integration with minimal infrastructure management.
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).
G2 Reviews:
What I like about AWS Glue
My team build a framework to fetch data from different platform through AWS Glue and stores them in S3 in the file format mention by us. That make our integration and fetching data a lot easier.
What I dislike about AWS Glue
Does not support xml file formats.
What is Meltano
Meltano is an open-source data integration platform, similar to Airbyte, that enables businesses to build and manage their own data pipelines. It offers a wide range of connectors for databases, APIs, application logs, and other data sources. Meltano also supports robust data transformation and orchestration capabilities, making it easier to customize and automate workflows. It integrates seamlessly with popular cloud data warehouses, making it a flexible choice for modern data teams looking to manage their end-to-end data stack.
Pros
- Open-source platform
- A really large number of connectors through Singer
- Offer an SDK to more easily build Singer taps and targets
- Flexibility in Deployment
Cons
- No fully managed options so you need to deploy yourself (in Beta though)
- Requires high maintenance
- Limited data transformation capabilities (only through deep integration with DBT)
- Only has a limited number of connectors that are natively built outside of Singer
As a user on G2 puts it::
What I like about Meltano
All the managerial tasks are handled under the hood, leaving you to focus on getting or consuming the data you need.
What I dislike about Meltano
With so many features baked into Meltano, navigating the documentation can be challenging. However, I've gotten around this by using Bing AI search, which brings me the answer immediately.
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
- Lineage, orchestration, and workflow features
- Ability to handle large datasets and near real-time data sync
- ETL + reverse ETL in one
- User-friendly and easy to set up
- Flat monthly pricing model
- 200+ connectors (Shopify, HubSpot, etc.)
- AI assistant
Cons
- Requires some technical knowledge around data warehousing and SQL
- Limited features for advanced data teams
- Focused on cloud data warehouses
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.
Feature-by-Feature Comparison
Ease of Use & 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.
Meltano
Meltano is simple and easy to use for those with technical expertise, particularly due to its portability and command-line usability, but may be challenging for less technical users.
Pricing & 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.
Meltano
Meltano is open-source and free to use, making it highly affordable, but requires significant investment in deployment and maintenance, especially without a fully managed option.
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.
Meltano
The platform offers extensive integration options, including support for data transformation and orchestration, but relies heavily on the Singer framework, which can limit capabilities.
Flexibility & 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.
Meltano
Meltano is highly flexible for advanced users who can manage their own deployments and build on the platform, but it requires substantial maintenance and lacks a fully managed option.
Summary of AWS Glue vs Meltano vs Weld
| Weld | AWS Glue | Meltano | |
|---|---|---|---|
| Connectors | 200+ | 50+ | 600+ |
| Price | $79 / 5M Active Rows | $0.44 per DPUs-hour (development endpoints) + per-job costs | free (self-hosted), custom (managed), paid support packages |
| Free tier | No | Yes | Yes |
| Location | EU | AWS Global (multi-region) | US |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
| Transformations | Yes | Yes | No |
| AI Assistant | Yes | No | No |
| On-Premise | No | No | Yes |
| Orchestration | Yes | Yes | Yes |
| Lineage | Yes | Yes | No |
| Version control | Yes | No | No |
| Load data to and from Excel | Yes | Yes | No |
| Load data to and from Google Sheets | Yes | No | No |
| 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 | 4.9 |
Conclusion
You’re comparing AWS Glue, Meltano, 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. .
- Meltano: the platform offers extensive integration options, including support for data transformation and orchestration, but relies heavily on the singer framework, which can limit capabilities.. meltano is open-source and free to use, making it highly affordable, but requires significant investment in deployment and maintenance, especially without a fully managed option..
- 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 $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..
