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Comparing Qlik Replicate with Rivery and Weld

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

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Weld vs Qlik Replicate vs Rivery

WeldQlik ReplicateRivery
Connectors200+100+200+
Price$99 / 5M Active RowsSubscription/perpetual license (custom quotes; six-figure enterprise costs)$0.75 per credit *100MB of data replication
Free tier
LocationEUKing of Prussia, PA, USA (Qlik HQ)US
Extract data (ETL)
Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL)
Transformations
AI Assistant
On-Premise
Orchestration
Lineage
Version control
Load to/from Excel
Load to/from Google Sheets
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating4.84.74.7

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).

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Pros

  • High-performance CDC with minimal source impact; supports heterogeneous sources and targets.

  • Automated schema change handling—table/column additions in source auto-reflected in target.

  • GUI-based configuration for tasks, monitoring dashboards, and robust error handling.

  • Cloud-native or on-prem installations; integrates with Qlik’s broader ecosystem (e.g., Qlik Sense).

Cons

  • No built-in ELT/transformations—only replication. Users need a separate tool for data transformations.

  • Enterprise pricing (per-core licensing) can be high, particularly for large-scale replication across many tables.

  • Learning curve for setting up advanced replication scenarios (e.g., multi-target replication, filters).

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 ...

Overview

Rivery in Short

Rivery is a SaaS-based ELT data integration platform designed to simplify the process of loading data from a wide variety of sources, including custom API-based platforms, into your preferred data warehouse. Although Rivery does not support real-time, on-the-fly data transformations during the loading process, it compensates with powerful post-load transformation capabilities. This allows users to clean, shape, and enrich their data after it has been ingested, ensuring the data is ready for analysis. Rivery’s user-friendly interface and automation features make it a strong option for teams looking to streamline their data workflows without heavy coding.

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Pros

  • Supports custom integrations though native GUI

  • Has reverse ETL option

  • Supports Python

  • Has data transformation capabilities

  • Great customer support

Cons

  • Lack of advanced error handling features

  • Cannot transform data on the fly (ETL)

  • Complex pricing model

  • UI is lacking when working with larger complex pipelines

  • Product documentation is lacking

Reviews & Quotes

As a user on G2 puts it::

What I like about Rivery

As a data analyst, I find the tool really easy to use; it's intuitive how you connect to the different data sources and create your data pipelines.

What I dislike about Rivery

For first-time users, it would be good to have some demo buttons; still, if you are familiar with terms, you'll manage to navigate between windows.

Overview

Weld in Short

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.

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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

Reviews & Quotes

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

Feature
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Qlik Replicate

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Rivery

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Weld

Ease of Use & Interface

Side-by-side

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Qlik Replicate

The Qlik Replicate UI provides wizards to create replication tasks quickly, monitors latency and throughput, and auto-detects schema changes. Setup for common CDC tasks is straightforward, but advanced filtering and tuning require expertise.

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Rivery

Rivery is known for its ease of use, especially for data analysts who need to connect different data sources and create pipelines quickly. Its intuitive GUI makes setup straightforward.

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Weld

Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.

Pricing & Affordability

Side-by-side

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Qlik Replicate

The licensing model is per-engine/core, often starting at $50k+/year for smaller environments. While expensive, the high reliability and low-latency replication justify cost for mission-critical use cases.

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Rivery

Rivery's pricing is complex and based on credits, which may not be straightforward for all users. Costs can rise significantly with increased data usage.

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Weld

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.

Feature Set

Side-by-side

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Qlik Replicate

Features: CDC-based replication, automated schema drift handling, support for 100+ sources/targets (databases, mainframes, cloud), multi-target replication, and basic transformations (e.g., data type conversions). No deep transformation engine.

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Rivery

The platform supports custom integrations, Python scripting, and reverse ETL, making it versatile for various data integration needs, but lacks on-the-fly transformation capabilities.

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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.

Flexibility & Customization

Side-by-side

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Qlik Replicate

Users can configure advanced mapping rules, filters, and transformations (limited) via the UI or JSON configs. For deeper transforms, integrate with Qlik Compose or third-party ETL. Qlik Replicate can be automated via CLI and REST API.

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Rivery

Rivery offers flexibility in custom integrations and supports post-load transformations, but its user interface may lack robustness for managing larger, more complex pipelines.

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Weld

Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.

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