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Weld vs Estuary (Flow) vs Talend

You’re comparing Weld vs Estuary (Flow) vs Talend. Explore how they differ on connectors, pricing, and features. Ed Logo

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Weld vs Estuary (Flow) vs Talend

FeatureWeldEstuary (Flow)Talend
Core Platform
Price
$79 / 5M Active Rows
$0.50/GB consumed + per-connector fee
Custom price, volume based
Free tier
No
Yes
No
Location
DK, (EU)
US
US
Connectors & Sync
Connectors
200+
200+
100+
Extract data (ETL)
Yes
Yes
Yes
Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL)
Yes
No
No
Two-Way Sync
Yes
No
No
Transformations & AI
Transformations
Yes
Yes
Yes
AI Assistant
Yes
No
No
dbt Core Integration
Yes
Yes
No
dbt Cloud Integration
Yes
No
No
Governance & DevOps
Orchestration
Yes
Yes
Yes
Lineage
Yes
Yes
Yes
Version control
Yes
Yes
Yes
On-Premise
No
Yes
Yes
OpenAPI / Developer API
Yes
Yes
Yes
Integrations
Load to/from Excel
Yes
No
No
Load to/from Google Sheets
Yes
Yes
No
Ratings
G2 rating
4.8
4.8
4

Overview

Weld in Short

Weld is a unified ELT and data activation platform that combines ingestion, modeling, transformations, orchestration, lineage, and reverse ETL in a single SaaS interface. With premium in-house–built connectors, an intuitive UI, and near real-time syncs, Weld enables both technical and non-technical users to create and manage data workflows efficiently. Weld also includes an AI assistant to support SQL modeling, generate transformations, and streamline repetitive tasks. Teams can ingest data from a wide range of sources—including marketing platforms, CRMs, databases, Google Sheets, Excel, and APIs—into their cloud data warehouse and activate it back into business tools.

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Pros

  • Lineage, orchestration, and workflow features included by default

  • Handles large datasets and near real-time data sync

  • ELT and reverse ETL in one platform

  • User-friendly interface with minimal setup required

  • Flat, predictable monthly pricing model

  • 200+ in-house–built, high-quality connectors

  • AI assistant for modeling and transformations

Cons

  • Some SQL knowledge is useful for advanced modeling

  • Optimized for cloud-warehouse workflows (Snowflake, BigQuery, Redshift, etc.)

  • Feature set is streamlined for modern ELT/activation use cases

Reviews & Quotes

A reviewer on G2 said:

What I like about Weld

Weld’s graphical interface is intuitive and easy to work with, even for teams with limited SQL experience. Its flexibility across sources—from databases to Google Sheets and APIs—made onboarding smooth, and performance across larger workloads was consistently strong. Support was responsive and helpful throughout our setup and ongoing use.

Overview

Estuary (Flow) in Short

Estuary Flow is a real-time ETL/ELT and data integration platform that supports both streaming and batch pipelines. It offers sub-second CDC ingestion, automated schema evolution, and a mix of no-code and low-code connectors. Estuary can deliver data to warehouses, lakes, BI tools, and operational systems, and supports both cloud and bring-your-own-cloud deployments.

estuary logo

Pros

  • Optimized for real-time ingestion using CDC with low-latency streaming.

  • Automated schema evolution and strong data consistency guarantees.

  • 200+ connectors for SaaS apps, databases, and messaging systems.

  • Supports multiple deployment models, including bring-your-own-cloud.

  • Supports SQL and TypeScript for transformation logic.

Cons

  • Consumption-based pricing can become expensive as data volume grows.

  • Connector coverage is expanding but may lack niche or emerging APIs.

  • Smaller community compared to some longstanding open-source tools.

  • More advanced streaming features require technical familiarity.

Reviews & Quotes

Estuary Pricing Page:

What I like about Estuary (Flow)

Estuary’s real-time, no-code model allows pipelines to be set up quickly with minimal maintenance, and the platform’s support team is highly responsive.

What I dislike about Estuary (Flow)

Pricing may be high for smaller teams, and less common connectors sometimes require additional development before they are production-ready.

Overview

Talend in Short

Talend is now part of Qlik and forms the foundation of the Qlik Talend Data Integration and Data Quality suite. The platform includes Talend Data Fabric and Qlik Talend Cloud, offering data integration, data quality, governance, application integration, and API management. It supports both ETL and ELT patterns and provides deployment flexibility across cloud, on-premise, and hybrid environments. Talend is generally positioned for larger or more mature data teams that need broad capabilities rather than a simple plug-and-play pipeline tool.

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Pros

  • Large set of enterprise-grade connectors and integration patterns

  • Supports ETL, ELT, APIs, and real-time pipelines

  • Strong data quality and governance capabilities

  • Flexible deployment: cloud, hybrid, and on-premise

  • Advanced features suitable for complex enterprise environments

Cons

  • Complex and harder to use for non-technical users

  • Pricing is custom and often expensive for smaller teams

  • Implementation can require significant setup and ongoing maintenance

  • More capabilities than needed for simple or mid-market workflows

Reviews & Quotes

As a reviewer on Gartner states: :

What I like about Talend

We are satisfied with Qlik Talend cloud, it enabled for us a seamless data integration and transformation, thanks to the tight integration with Qlik Cloud analytics.

What I dislike about Talend

It's a very good tool however this tool is better for data migration and a little lacking/ or difficult to use when it comes to some cleansing or further analysis.

Feature-by-Feature Comparison

Feature
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estuary logo
talend logo

Ease of Use & Interface

Side-by-side

weld logo

Weld’s interface is built for clarity and speed, enabling users with varying levels of technical experience to manage data pipelines and models efficiently. Its built-in lineage and orchestration tools provide transparency across workflows.

estuary logo

Estuary offers a clean interface for configuring CDC streams, destinations, and transformations. Most pipelines can be built through no-code connectors, while more advanced logic can be defined using SQL or TypeScript within the Flow editor.

talend logo

Talend has a steep learning curve, especially for non-technical users, due to its extensive feature set and advanced capabilities, which require significant training and experience to utilize fully.

Pricing & Affordability

Side-by-side

weld logo

Weld offers a simple and predictable pricing model starting at $79 for 5 million active rows. This flat, usage-transparent structure makes budgeting straightforward for small and medium-sized teams.

estuary logo

Estuary includes a free tier with 10 GB per month and a 30-day trial. The consumption-based model provides flexibility but can become costly at high data volumes or for continuous streaming workloads.

talend logo

Talend's pricing is custom and can be expensive, especially for small businesses. It requires a substantial upfront investment, making it more suitable for large enterprises with significant data needs.

Feature Set

Side-by-side

weld logo

Weld provides ELT ingestion, SQL-based transformations, reverse ETL activation, data lineage, orchestration, and workflow management in a single platform. Its AI assistant accelerates modeling and transformation tasks.

estuary logo

Key capabilities include streaming and batch ETL, CDC with low latency, automated schema evolution, in-stream SQL or TypeScript transformations, dbt compatibility, and support for Kafka-style messaging. It also provides data replay features through persisted storage.

talend logo

Talend offers a robust feature set with a large number of connectors, supporting both ELT and ETL capabilities, along with options for on-premise deployments. It is well-suited for mature data teams needing comprehensive data integration and management.

Flexibility & Customization

Side-by-side

weld logo

Users can model data using SQL enhanced by Weld’s AI assistant, automate workflows, and build custom connectors to any API. This provides strong flexibility for teams that want to tailor integrations and transformations within one platform.

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Users can write custom TypeScript transformations in-stream or use SQL at the destination. Pipelines can be managed through the CLI and integrated with CI/CD processes. Custom connectors can be built using the open-source Flow SDK, providing extensibility beyond the pre-built catalog.

talend logo

Talend provides flexibility and customization options, making it ideal for large enterprises with complex data needs. However, this comes at the cost of ease of use, particularly for less experienced users.

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CUSTOMER STORIES

The latest success stories from data-driven companies

Jacob Poulsen, Head of Marketing Expansion at Flatpay logo

How Flatpay optimized marketing efficiency with Weld

One of the biggest impacts has been unlocking new ways to buy media. Before, we didn’t have the data to back up strategic decisions – now we do.
Jacob Poulsen, Head of Marketing Expansion at Flatpay
Rodrigo Andres Valle, Data Engineer at Holafly logo

How Holafly transformed data management and scaled globally with Weld

Before Weld, we had to rely on custom Python scripts and manual processes that were time-consuming and error-prone.
Rodrigo Andres Valle, Data Engineer at Holafly
Michael Howes, Head of Data & Insights at Dishoom logo

How Dishoom scaled data operations without scaling its team

We’re still a team of three, but we’re often doing far more than the equivalent of three full-time employees. That’s down to how we're able to leverage systems, data, and processes.
Michael Howes, Head of Data & Insights at Dishoom
Sven Hasenberg, CFO, VitaMoment logo

Inside VitaMoment’s Journey to KPI-Driven Growth and Data Ownership

We’ve always been a KPI-driven company. But we wanted to scale that mindset across every team member, every team, every decision.
Sven Hasenberg, CFO, VitaMoment
Temur Makhsudov, Head of BI and Operations logo

How Danish Endurance boosted profitability by 77 % and transformed data management with Weld

Before Weld, our data infrastructure was limited and we relied heavily on Excel files and custom Python scripts.
Temur Makhsudov, Head of BI and Operations
Matias Voldby Drejer, BI Lead logo

How Female Invest centralized data management and saved resources with Weld

Weld has saved us a ton of time, from not having data ready to having a fully functional data warehouse and connectors.
Matias Voldby Drejer, BI Lead
Jonas Iversen, Tech Lead Data logo

How Soundboks streamlined data integration with Weld, S3, and Databricks

By integrating Weld, Amazon S3, and Databricks, Soundboks built a modern data pipeline that automates data ingestion, improves reporting, and provides up-to-date visibility into sales performance
Jonas Iversen, Tech Lead Data
Jens Karstoft, Chief Operating Officer at Roccamore logo

How Roccamore unlocked better business insights with Weld

We didn’t have a good data setup, so we lacked the business insights we needed. Weld has allowed us to set up a structured data infrastructure and access insights quickly.
Jens Karstoft, Chief Operating Officer at Roccamore

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