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Weld vs Fivetran vs Qlik Replicate

You’re comparing Weld vs Fivetran vs Qlik Replicate. Explore how they differ on connectors, pricing, and features. Ed Logo

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Fivetran logo
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Weld vs Fivetran vs Qlik Replicate

FeatureWeldFivetranQlik Replicate
Core Platform
Price
$79 / 5M Active Rows
Usage-based: charged by Monthly Active Rows and model runs.
Custom licensing (subscription or perpetual); typically high enterprise cost
Free tier
No
Yes
No
Location
DK, (EU)
US
King of Prussia, PA, USA
Connectors & Sync
Connectors
200+
740+
100+
Extract data (ETL)
Yes
Yes
No
Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL)
Yes
Yes
No
Two-Way Sync
Yes
No
No
Transformations & AI
Transformations
Yes
Yes
No
AI Assistant
Yes
No
No
dbt Core Integration
Yes
Yes
No
dbt Cloud Integration
Yes
Yes
No
Governance & DevOps
Orchestration
Yes
Yes
Yes
Lineage
Yes
Yes
No
Version control
Yes
No
No
On-Premise
No
Yes
Yes
OpenAPI / Developer API
Yes
Yes
Yes
Integrations
Load to/from Excel
Yes
Yes
No
Load to/from Google Sheets
Yes
Yes
No
Ratings
G2 rating
4.8
4.2
4.7

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

Fivetran in Short

Fivetran is a well-established ELT tool focused on automating data ingestion through prebuilt connectors. It supports transformation orchestration and reverse ETL via its acquisition of Census. While it’s widely used in enterprise settings, its reliance on SQL-based workflows and external tools can increase complexity and cost for teams without dedicated data engineering resources.

Fivetran logo

Pros

  • Large library of prebuilt connectors (740+)

  • Support for dbt-based transformations

  • Reverse ETL through Census integration

  • Option for hybrid deployment in sensitive environments

  • Granular access control and metadata logging

Cons

  • Usage-based pricing can escalate quickly

  • Transformations require SQL and dbt expertise

  • Limited flexibility in Quickstart models

  • No support for AI-assisted SQL generation

  • Reverse ETL is managed via a separate product (Census)

Reviews & Quotes

From a review on G2:

What I like about Fivetran

The pre-built connectors make data integration super easy, without the need for an expensive data engineering team. If you're using dbt, there's a package for most connectors that gives you ready-to-go data models.

What I dislike about Fivetran

New connectors are released infrequently, and pricing can be opaque. If you're not already using a modern data stack with their preferred tools, integration can be tricky.

Overview

Qlik Replicate in Short

Qlik Replicate (formerly Attunity) is a change data capture (CDC) and replication platform that moves data in real-time from databases, mainframes, and cloud sources into data warehouses, data lakes, and analytics platforms. It provides a graphical UI to configure replication tasks, automated schema change handling, and supports a wide range of sources (Oracle, SQL Server, DB2, MongoDB) and targets (Snowflake, Redshift, BigQuery, Kafka).

qlik logo

Pros

  • High-performance CDC with low impact on source systems; broad support for heterogeneous sources and targets.

  • Automated schema-change handling with minimal manual intervention.

  • GUI-based task configuration, monitoring dashboards, and detailed error handling.

  • Supports on-premise and cloud deployments; integrates with Qlik’s broader platform ecosystem.

Cons

  • No ELT or complex transformation engine—primarily replication only.

  • Enterprise licensing can be expensive, especially at high volumes or across many tables.

  • Advanced replication scenarios (e.g., multi-target, filtering) require more expertise.

Reviews & Quotes

Gartner Peer Review:

What I like about Qlik Replicate

Meets data replication needs. Ability to 'read once write many' i.e. fork out data to multiple targets is a major plus.

What I dislike about Qlik Replicate

Vendor need to work on enhancing capabilities e.g. Enabling additional ...

Feature-by-Feature Comparison

Feature
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Fivetran logo
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Ease of Use & Interface

Side-by-side

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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.

Fivetran logo

Fivetran simplifies initial ingestion setup, but configuration and transformation workflows depend heavily on SQL and dbt. Teams without this experience may face a steeper learning curve.

qlik logo

Qlik Replicate offers a visual interface for configuring CDC and replication tasks, monitoring latency, and validating throughput. Core replication setup is straightforward, while advanced tuning and filtering can require deeper expertise.

Pricing & Affordability

Side-by-side

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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.

Fivetran logo

Fivetran’s MAR-based pricing model makes it difficult to predict costs, especially for teams with growing or unpredictable data volumes.

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Licensing is typically per-core or per-engine and often starts in the tens of thousands annually. While costly, organizations with mission-critical replication workloads often find the reliability and low-latency performance justify the investment.

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.

Fivetran logo

Fivetran includes ELT, dbt-based transformations, and reverse ETL via Census. It also provides orchestration via API, Terraform, and Airflow, though customization is oriented toward technical users.

qlik logo

Provides real-time CDC replication, schema-change handling, multi-target replication, support for 100+ enterprise sources and destinations, and basic transformation options such as data-type mapping. Not intended as a full ETL platform.

Flexibility & Customization

Side-by-side

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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.

Fivetran logo

While programmatic and infrastructure-based extensibility is supported, the platform lacks low-code or guided transformation features, limiting accessibility for non-engineering teams.

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Advanced filtering, transformation rules, and mappings can be configured through the UI or JSON task definitions. Automation is available through CLI and REST API. For complex ELT/ETL needs, users typically pair Replicate with Qlik Compose or a third-party tool.

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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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