Comparing Estuary with Stitch and Weld
Carolina Russ6 min read
What is Estuary
Estuary Flow is a real-time ETL/ELT and data integration platform for both batch and streaming pipelines. It provides sub-100ms latency using Change Data Capture (CDC), supports automated schema evolution, and allows users to build entire pipelines with low- or no-code connectors in minutes. It can target data warehouses (e.g., Snowflake, BigQuery), BI tools, and operational systems for analytics, operations, and AI use cases.
Pros
- Purpose-built for real-time CDC and streaming ETL with sub-100ms latency.
- Automatic schema evolution with exactly-once delivery guarantees.
- 200+ no-code connectors for databases, SaaS apps, and message queues.
- Flexible deployment: public cloud, private cloud, or self-hosted (BYOC).
Cons
- Premium pricing model ($0.50/GB consumed + connector fees) can be expensive for small teams.
- Still growing connector catalog; niche or very new APIs may require custom work.
- Smaller community compared to older open-source tools, meaning fewer community-built resources.
Estuary Pricing Page:
What I like about Estuary
Estuary’s real-time, no-code model is magical—getting data instantly with minimal effort and near-zero pipeline maintenance. Plus, their support is fantastic.
What I dislike about Estuary
Pricing can be high for lower-volume teams, and some less-common connectors are still in development, which limits immediate use cases for niche sources.
What is Stitch
Acquired by Talend in 2018, Stitch Data is a cloud open-source and developer-focused ELT platform that offers no-code connectors to bring data into your warehouse. Stitch offers compatibility with a broad range of data sources and destinations. It also enables customers to construct new sources based on Singer's standards, an open-source toolkit designed for scriptwriting.
Pros
- Easy to setup and use
- A cost-friendly pricing model that's easy to understand and based on usage
- Integrates with Talend
- Includes transformations with JSON
- Fully managed no-code ELT data pipelines
Cons
- Require deep technical knowledge to get full value out of the platform
- The quality can vary a lot between different connectors as they are not maintained by Stitch
- Depends on the Singer open source framework which can break without notice
A reviewer on Gartner said::
What I like about Stitch
Stitch is an affordable tool for bringing data "as is" from the various data sources (Google Ads, Salesforce or even MySQL) to a data warehouse (Redshift, Snowflake, BigQuery, etc.)
What I dislike about Stitch
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.
Estuary vs Stitch: Ease of Use and User Interface
Estuary
Estuary’s UI is intuitive: users can add connectors, configure CDC streams, and specify destinations in a few clicks. Complex transformations can be written in SQL or TypeScript directly in the Flow editor, but most tasks are handled via no-code connectors.
Stitch
Stitch is relatively easy to set up and use, offering no-code connectors and an affordable pricing model, but users may need deep technical knowledge to leverage its full potential.
Estuary vs Stitch: Pricing Transparency and Affordability
Estuary
While Estuary provides a 10 GB/month free tier and a 30-day trial, its consumption-based pricing ($0.50/GB + connector fees) can become costly at scale. Teams processing hundreds of GBs per month should budget accordingly.
Stitch
Stitch's pricing model is cost-friendly and based on usage, making it accessible for many users. However, costs can increase if data volumes grow significantly.
Estuary vs Stitch: Comprehensive Feature Set
Estuary
Key features include real-time CDC (sub-100ms latency), batch and streaming pipelines, automated schema evolution, and in-stream or post-load transformations via SQL/TypeScript or dbt. It also supports Kafka-compatibility and private storage for data replay.
Stitch
Stitch offers fully managed no-code ELT data pipelines and integrates with Talend, but relies heavily on the Singer open-source framework, which can be less stable.
Estuary vs Stitch: Flexibility and Customization
Estuary
Estuary allows custom TypeScript transforms in-stream or SQL in-destination. Pipelines can be managed via CLI (flowctl) and integrated into CI/CD. While most connectors are no-code, custom connectors can be built using the open-source Flow SDK.
Stitch
Stitch is designed for simplicity and ease of use, but customization is limited and dependent on the capabilities of the open-source Singer framework.
Summary of Estuary vs Stitch vs Weld
| Weld | Estuary | Stitch | |
|---|---|---|---|
| Connectors | 200++ | 200+ | 140+ |
| Price | $99 / Unlimited usage | $0.50/GB consumed + per-connector fee | $100 / 5M rows |
| Free tier | No | Yes | Yes |
| Location | EU | New York, NY, USA | US |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
| Transformations | Yes | Yes | Yes |
| AI Assistant | Yes | No | No |
| On-Premise | No | Yes | No |
| Orchestration | Yes | Yes | No |
| Lineage | Yes | Yes | No |
| Version control | Yes | Yes | No |
| Load data to and from Excel | Yes | No | No |
| Load data to and from Google Sheets | Yes | Yes | No |
| Two-Way Sync | Yes | No | No |
| dbt Core Integration | Yes | Yes | Yes |
| dbt Cloud Integration | Yes | No | No |
| OpenAPI / Developer API | Yes | Yes | Yes |
| G2 Rating | 4.8 | 4.8 | 4.5 |
Conclusion
You’re comparing Estuary, Stitch, Weld. Each of these tools has its own strengths:
- Estuary: key features include real-time cdc (sub-100ms latency), batch and streaming pipelines, automated schema evolution, and in-stream or post-load transformations via sql/typescript or dbt. it also supports kafka-compatibility and private storage for data replay. . while estuary provides a 10 gb/month free tier and a 30-day trial, its consumption-based pricing ($0.50/gb + connector fees) can become costly at scale. teams processing hundreds of gbs per month should budget accordingly. .
- Stitch: stitch offers fully managed no-code elt data pipelines and integrates with talend, but relies heavily on the singer open-source framework, which can be less stable.. stitch's pricing model is cost-friendly and based on usage, making it accessible for many users. however, costs can increase if data volumes grow significantly..
- 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..
