Comparing 5X with Mozart Data and Weld



What is 5X
Pros
- 500+ connectors for both source and destination (data warehouses, SaaS apps, ad platforms, etc.).
- Includes managed Snowflake/BigQuery warehouse, dbt core integration for transformations, and reverse ETL to push data back to apps—all in one platform.
- Built-in BI layer and semantic metric definitions so you can build dashboards without a separate BI tool.
- Dedicated in-house data experts provide consulting and implementation support, accelerating time-to-value.
Cons
- Premium pricing (Starter ~$500/mo, scaling with connectors/warehouse usage) can be high for small teams.
- Being a newer startup, the community and third-party tutorials are limited; some advanced features are still maturing.
- Heavily opinionated stack—if you use an alternate data warehouse or BI tool, integration can require workarounds.
5X Testimonials:
What I like about 5X
5X’s all-in-one stack reduced our tool sprawl: data ingested, transformed, and even dashboards were live in days. Their in-house experts helped us onboard quickly.
What I dislike about 5X
As a relatively new entrant, some advanced features (e.g., AI-driven pipeline suggestions) are still in beta, and pricing can scale up quickly with heavy usage.
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.
5X vs Mozart Data: Ease of Use and User Interface
5X
5X’s UI guides users through onboard: connect sources, choose warehouse, define dbt models, and build dashboards—all via a low-code interface. Non-technical users can leverage pre-packaged templates, while power users can write custom SQL/dbt.
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.
5X vs Mozart Data: Pricing Transparency and Affordability
5X
5X offers a Free Forever tier for small usage (limited connectors/rows). The Starter plan (~$500/mo) covers basic use, but costs increase with data volume and connector count. ROI calculations often justify the cost by consolidating multiple tools.
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.
5X vs Mozart Data: Comprehensive Feature Set
5X
End-to-end features: ETL ingestion (500+ connectors), managed warehouse provisioning, dbt transformations, reverse ETL, built-in BI/visualization, and a semantic layer. It also includes lineage tracking and API endpoints for data apps.
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.
5X vs Mozart Data: Flexibility and Customization
5X
While 5X is tightly integrated, it allows custom dbt models, Python UDFs, and can ingest data from arbitrary APIs. If you don’t need the BI layer, you can skip that component. Custom connectors can be built upon request by their team.
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 5X vs Mozart Data vs Weld
Weld | 5X | Mozart Data | |
---|---|---|---|
Connectors | 200++ | 500+ | 150+ |
Price | €99 / Unlimited usage | Free Forever tier; Starter ~$500/month for limited usage, then scales with volume | Starts around $1,000/mo (includes Snowflake + ETL up to 250k MAR) |
Free tier | No | Yes | Yes |
Location | EU | Singapore (HQ) + USA, UK, India | San Francisco, CA, USA |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | Yes | No |
Transformations | Yes | Yes | Yes |
AI Assistant | Yes | No | No |
On-Premise | No | No | No |
Orchestration | Yes | Yes | Yes |
Lineage | Yes | Yes | No |
Version control | Yes | Yes | No |
Load data to and from Excel | Yes | Yes | Yes |
Load data to and from Google Sheets | Yes | Yes | Yes |
Two-Way Sync | Yes | Yes | No |
dbt Core Integration | Yes | Yes | Yes |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | No | No |
G2 Rating | 4.8 | 4.9 | 4.6 |
Conclusion
You’re comparing 5X, Mozart Data, Weld. Each of these tools has its own strengths:
- 5X: end-to-end features: etl ingestion (500+ connectors), managed warehouse provisioning, dbt transformations, reverse etl, built-in bi/visualization, and a semantic layer. it also includes lineage tracking and api endpoints for data apps. . 5x offers a free forever tier for small usage (limited connectors/rows). the starter plan (~$500/mo) covers basic use, but costs increase with data volume and connector count. roi calculations often justify the cost by consolidating multiple tools. .
- 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..