Comparing Databox with Qlik Replicate and Weld
Carolina Russ6 min read
What is Databox
Databox is a cloud-based data visualization and business intelligence platform that helps businesses of all sizes track, analyze, and share their key performance indicators (KPIs). It offers a wide range of features, including the ability to connect to multiple data sources, create custom dashboards, and share insights with others.
Pros
- Easy to use
- Powerful features
- Great customer support
- Comprehensive data visualization
- Real-time data updates
Cons
- Expensive
- Limited customization
- Lack of advanced features
- Limited drill-down capabilities
A reviewer on Capterra:
What I like about Databox
Databox is always looking for ways to improve its interface. It's smooth - data updates quickly and it's easy to use. The customer service is super responsive, and always willing to step in and help out with the Databoards (dashboards) I'm working on. I would say it is my favorite tool to use as an analyst - ever!
What I dislike about Databox
Still missing some more obscure, less popular, integrations.
What is Qlik Replicate
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).
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).
Qlik Replicate Documentation:
What I like about Qlik Replicate
Replicate’s CDC capabilities ensure minimal latency and zero-impact on source databases. Schema changes in the source are automatically captured and propagated to targets.
What I dislike about Qlik Replicate
Licensing is expensive, and it’s focused solely on replication (no transformations). For broader ETL, additional tools are needed.
What is Weld
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.
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.
Databox vs Qlik Replicate: Ease of Use and User Interface
Databox
Databox is easy to use with a smooth interface and real-time data updates, making it a favorite among analysts for data visualization and reporting.
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.
Databox vs Qlik Replicate: Pricing Transparency and Affordability
Databox
Databox is on the pricier side, which might deter smaller businesses or startups with limited budgets, despite its robust features and customer support.
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.
Databox vs Qlik Replicate: Comprehensive Feature Set
Databox
The platform offers powerful data visualization tools and comprehensive dashboards, but lacks advanced features and customization options, which could be limiting for some users.
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.
Databox vs Qlik Replicate: Flexibility and Customization
Databox
Databox provides a range of data visualization tools, but customization is limited, particularly for more complex reporting and analysis needs.
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.
Summary of Databox vs Qlik Replicate vs Weld
| Weld | Databox | Qlik Replicate | |
|---|---|---|---|
| Connectors | 200+ | 100+ | 100+ |
| Price | €99 / 2 connectors | €47 / month - 3 sources, 5 users | Subscription/perpetual license (custom quotes; six-figure enterprise costs) |
| Free tier | No | Yes | No |
| Location | EU | US | King of Prussia, PA, USA (Qlik HQ) |
| Extract data (ETL) | Yes | Yes | No |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
| Transformations | Yes | No | No |
| AI Assistant | Yes | No | No |
| On-Premise | No | No | Yes |
| Orchestration | Yes | No | Yes |
| Lineage | Yes | No | No |
| Version control | Yes | No | No |
| Load data to and from Excel | Yes | No | No |
| Load data to and from Google Sheets | Yes | No | No |
| Two-Way Sync | Yes | No | No |
| dbt Core Integration | Yes | No | No |
| dbt Cloud Integration | Yes | No | No |
| OpenAPI / Developer API | Yes | No | Yes |
| G2 Rating | 4.8 | 4.5 | 4.7 |
Conclusion
You’re comparing Databox, Qlik Replicate, Weld. Each of these tools has its own strengths:
- Databox: the platform offers powerful data visualization tools and comprehensive dashboards, but lacks advanced features and customization options, which could be limiting for some users.. databox is on the pricier side, which might deter smaller businesses or startups with limited budgets, despite its robust features and customer support..
- 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. . 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: 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..
