Comparing Estuary with Jitterbit and Weld



What is Estuary
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 Jitterbit
Pros
- Pre-built connectors for CRM, ERP, databases, and flat files; plus the ability to build custom connectors via SDK.
- API creation feature: turn data flows into REST or SOAP endpoints on the fly.
- Visual Studio for designing Jitterpaks (pipelines), with drag-and-drop mapping and transformation steps.
- Real-time and batch modes supported; can deploy on Jitterbit’s cloud or your own servers (hybrid).
Cons
- Complex licensing (based on endpoints, environments, and usage) can be expensive for heavy data volumes.
- Studio interface can feel less modern compared to newer iPaaS; large, complex flows can become unwieldy.
- Some advanced transformations require writing custom code rather than purely using GUI.
Jitterbit Harmony Overview:
What I like about Jitterbit
Jitterbit’s Studio UI makes building integrations straightforward, and the API creation feature lets us expose data to external apps quickly.
What I dislike about Jitterbit
Pricing is tiered and can be high as you add more endpoints or data volume. Complex transformations sometimes require scripting, despite the low-code interface.
What is Weld
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 Jitterbit: 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.
Jitterbit
Jitterbit’s Studio is a Java-based desktop application (also has a web version) with a canvas for designing operations. It supports mapping between schemas, scripting for complex logic, and testing within the UI. Some users find it less responsive for very large flows.
Estuary vs Jitterbit: 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.
Jitterbit
Pricing depends on number of endpoints, environments (dev/test/prod), and data volume. Smaller teams might start around $25k/year, but enterprise usage can cost significantly more.
Estuary vs Jitterbit: 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.
Jitterbit
Features include: ETL/ELT pipelines, API generation, cloud & on-prem deployment, real-time event triggers, pre-built templates (“Jitterpaks”), and monitoring dashboards. Also supports multi-environment promotion and CI/CD.
Estuary vs Jitterbit: 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.
Jitterbit
Users can embed JavaScript or VBScript for transformations. Jitterbit’s SDK allows building custom connectors. While hybrid deployment is possible, full feature access often requires cloud usage.
Summary of Estuary vs Jitterbit vs Weld
Weld | Estuary | Jitterbit | |
---|---|---|---|
Connectors | 200++ | 200+ | 100+ |
Price | $99 / Unlimited usage | $0.50/GB consumed + per-connector fee | Subscription-based (custom quotes; starts ~$25k/year) |
Free tier | No | Yes | No |
Location | EU | New York, NY, USA | Oakland, CA, USA |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | Yes |
Transformations | Yes | Yes | Yes |
AI Assistant | Yes | No | No |
On-Premise | No | Yes | Yes |
Orchestration | Yes | Yes | Yes |
Lineage | Yes | Yes | No |
Version control | Yes | Yes | Yes |
Load data to and from Excel | Yes | No | Yes |
Load data to and from Google Sheets | Yes | Yes | No |
Two-Way Sync | Yes | No | Yes |
dbt Core Integration | Yes | Yes | No |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | Yes | Yes |
G2 Rating | 4.8 | 4.8 | 4.3 |
Conclusion
You’re comparing Estuary, Jitterbit, 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. .
- Jitterbit: features include: etl/elt pipelines, api generation, cloud & on-prem deployment, real-time event triggers, pre-built templates (“jitterpaks”), and monitoring dashboards. also supports multi-environment promotion and ci/cd. . pricing depends on number of endpoints, environments (dev/test/prod), and data volume. smaller teams might start around $25k/year, but enterprise usage can cost significantly more. .
- 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..