Comparing Databox with Mozart Data and Weld



What is Databox
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 Mozart Data
Pros
- Out-of-the-box Snowflake data warehouse with connectors and dbt transforms in one package.
- 150+ connectors (via embedded Fivetran + Portable) configured behind the scenes so you don’t manage separate tools.
- Very fast onboarding—your data stack is live in under an hour without any code.
- Dedicated customer support and onboarding assistance (Mozart Assist) helps users set up and maintain pipelines.
Cons
- Pricing includes both warehouse usage and data volume (Monthly Active Rows), so costs rise with scale—often more expensive than self-managed ELT at high volumes.
- Less flexibility for bespoke connector logic—if a connector is missing, you must submit a request and wait for their team.
- Smaller community and fewer third-party tutorials compared to standalone tools like Airbyte or dbt.
Mozart Data Reviews (G2):
What I like about Mozart Data
Mozart Data gave us a turnkey stack with Snowflake, connectors, and transformations all configured. We were running dashboards in under a week without DevOps overhead.
What I dislike about Mozart Data
Costs can escalate quickly with high data volumes, and adding niche connectors often requires a request to their team (no self-serve).
What is Weld
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 Mozart Data: 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.
Mozart Data
Mozart Data abstracts away infrastructure: users pick sources via a web UI, configure destinations, and their warehouse and pipelines spin up automatically. Minimal learning curve for non-technical teams.
Databox vs Mozart Data: 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.
Mozart Data
Mozart’s bundled pricing (data volume + warehouse compute) starts at ~$1,000/month for small usage, which can be competitive for teams that value time saved over cost. However, high-volume users may find it pricier than DIY stacks.
Databox vs Mozart Data: 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.
Mozart Data
Includes managed Snowflake, automated ETL connectors (via Fivetran + Portable), a dbt transformation layer, and monitoring dashboards. Supports scheduling, incremental loads, and basic orchestrations without separate tools.
Databox vs Mozart Data: Flexibility and Customization
Databox
Databox provides a range of data visualization tools, but customization is limited, particularly for more complex reporting and analysis needs.
Mozart Data
While Mozart Data handles most common use cases seamlessly, it limits custom code in pipelines. Advanced users can still bring their own SQL or dbt models, but building new connectors requires raising a request—no self-serve SDK.
Summary of Databox vs Mozart Data vs Weld
Weld | Databox | Mozart Data | |
---|---|---|---|
Connectors | 200++ | 100+ | 150+ |
Price | €99 / Unlimited usage | €47 / month - 3 sources, 5 users | Starts around $1,000/mo (includes Snowflake + ETL up to 250k MAR) |
Free tier | No | Yes | Yes |
Location | EU | US | San Francisco, CA, USA |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
Transformations | Yes | No | Yes |
AI Assistant | Yes | No | No |
On-Premise | No | No | No |
Orchestration | Yes | No | Yes |
Lineage | Yes | No | No |
Version control | Yes | No | No |
Load data to and from Excel | Yes | No | Yes |
Load data to and from Google Sheets | Yes | No | Yes |
Two-Way Sync | Yes | No | No |
dbt Core Integration | Yes | No | Yes |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | No | No |
G2 Rating | 4.8 | 4.5 | 4.6 |
Conclusion
You’re comparing Databox, Mozart Data, 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..
- Mozart Data: includes managed snowflake, automated etl connectors (via fivetran + portable), a dbt transformation layer, and monitoring dashboards. supports scheduling, incremental loads, and basic orchestrations without separate tools. . mozart’s bundled pricing (data volume + warehouse compute) starts at ~$1,000/month for small usage, which can be competitive for teams that value time saved over cost. however, high-volume users may find it pricier than diy stacks. .
- 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..