What I like about CloverDX
“Ability to design elegant data flows and work with really dirty data. The visual design ensures that you write proper rules to deal with a variety of data quality issues”
You’re comparing CloverDX vs Qlik Replicate vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | CloverDX | Qlik Replicate | |
|---|---|---|---|
| Connectors | 200+ | 150+ | 100+ |
| Price | $99 / 5M Active Rows | Subscription or perpetual licensing (custom quotes, typically $20k+ annually) | Subscription/perpetual license (custom quotes; six-figure enterprise costs) |
| Free tier | |||
| Location | EU | Culver City, CA, USA | King of Prussia, PA, USA (Qlik HQ) |
| Extract data (ETL) | |||
| Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL) | |||
| Transformations | |||
| AI Assistant | |||
| On-Premise | |||
| Orchestration | |||
| Lineage | |||
| Version control | |||
| Load to/from Excel | Yes (Excel/CSV) | ||
| Load to/from Google Sheets | Yes (via API) | ||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.2 | 4.7 |
Overview
CloverDX is an enterprise-grade ETL/ELT platform that emphasizes flexibility, automation, and scalability in designing complex data workflows. It supports both code-based and GUI-driven development, making it suitable for both developers and data engineers. It is also known for its transformation, data quality, and data migration capabilities. CloverDX helps to deliver a seamless onboarding process for clients, saving hours of manual work with automated conversion from any file format.

Metadata-driven: automatic handling of schema drift and impact analysis across pipelines.
Visual Graphical Data Mixer for building data flows, with reusable subgraphs and components.
Supports both batch and streaming ingestion, with connectors to databases, cloud storage, Hadoop, and REST APIs.
Built-in scheduling, monitoring dashboards, alerting, and role-based access control.
High licensing costs make it less suitable for smaller teams or startups.
Designer IDE can feel heavy and less intuitive for simple tasks; learning curve for new users.
Less community presence than open-source tools, so third-party resources and tutorials are limited.
Gartner Peer Review:
“Ability to design elegant data flows and work with really dirty data. The visual design ensures that you write proper rules to deal with a variety of data quality issues”
“Lack of support for AI, Machine learning, Neural networks and ability to run basic regression.”
Overview
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).

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).
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).
Gartner Peer Review:
“Meets data replication needs. Ability to 'read once write many' i.e. fork out data to multiple targets is a major plus.”
“Vendor need to work on enhancing capabilities e.g. Enabling additional ...”
Overview
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.
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
Requires some technical knowledge around data warehousing and SQL
Limited features for advanced data teams
Focused on cloud data warehouses
A reviewer on G2 said:
“Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.”




Side-by-side

CloverDX Designer is an Eclipse-based IDE where developers build data flow graphs. The drag-and-drop canvas is powerful but can feel cluttered for large projects. Reusable components and parameterization help, but initial learning is significant.

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.
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.
Side-by-side
CloverDX Designer is an Eclipse-based IDE where developers build data flow graphs. The drag-and-drop canvas is powerful but can feel cluttered for large projects. Reusable components and parameterization help, but initial learning is significant.
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.
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.
Side-by-side

CloverDX’s pricing is tiered by job servers, connector count, and features—often starting around $20k/year. Best for medium-to-large organizations requiring robust metadata handling and enterprise governance.

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.
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.
Side-by-side
CloverDX’s pricing is tiered by job servers, connector count, and features—often starting around $20k/year. Best for medium-to-large organizations requiring robust metadata handling and enterprise governance.
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.
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.
Side-by-side

Features include: visual data flow designer, metadata-driven transformations, automated schema evolution, batch & streaming support, job scheduling & monitoring, role-based access, and REST/JSON/XML connectors. Also offers advanced data quality and permutation-based testing.

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.
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.
Side-by-side
Features include: visual data flow designer, metadata-driven transformations, automated schema evolution, batch & streaming support, job scheduling & monitoring, role-based access, and REST/JSON/XML connectors. Also offers advanced data quality and permutation-based testing.
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.
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.
Side-by-side

Users can develop custom Java or Groovy components for specialized transformations, extend connectors via REST templates, and integrate with external schedulers. The open API allows embedding Clover DX in other applications.

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.
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.
Side-by-side
Users can develop custom Java or Groovy components for specialized transformations, extend connectors via REST templates, and integrate with external schedulers. The open API allows embedding Clover DX in other applications.
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.
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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