Comparing Mozart Data with Weld
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.
Mozart Data vs Weld: Ease of Use and User Interface
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.
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.
Mozart Data vs Weld: Pricing Transparency and Affordability
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.
Weld
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.
Mozart Data vs Weld: Comprehensive Feature Set
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.
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.
Mozart Data vs Weld: Flexibility and Customization
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.
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.
Summary of Mozart Data vs Weld
| Weld | Mozart Data | |
|---|---|---|
| Connectors | 200++ | 150+ |
| Price | $99 / Unlimited usage | Starts around $1,000/mo (includes Snowflake + ETL up to 250k MAR) |
| Free tier | No | Yes |
| Location | EU | San Francisco, CA, USA |
| Extract data (ETL) | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No |
| Transformations | Yes | Yes |
| AI Assistant | Yes | No |
| On-Premise | No | No |
| Orchestration | Yes | Yes |
| Lineage | Yes | No |
| Version control | Yes | No |
| Load data to and from Excel | Yes | Yes |
| Load data to and from Google Sheets | Yes | Yes |
| Two-Way Sync | Yes | No |
| dbt Core Integration | Yes | Yes |
| dbt Cloud Integration | Yes | No |
| OpenAPI / Developer API | Yes | No |
| G2 Rating | 4.8 | 4.6 |
Conclusion
When comparing Mozart Data and Weld, consider your primary requirements and budget:
- Mozart Data excels at 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. . If you need robust transformations and a wide connector catalogue with a strong focus on 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. , this may be your best choice.
- Weld offers competitive pricing and 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.. If you prioritize ease of setup, real-time syncing, or specific integrations, this tool could be a better fit.
