Comparing Blendo with Mozart Data and Weld



What is Blendo
Pros
- Quick setup for popular marketing and product analytics sources with pre-built dashboards.
- Handles incremental syncs and auto-updates when source schemas change.
- Offers a unified metrics layer with common definitions (e.g., MRR, CAC) out-of-the-box.
Cons
- Niche focus on marketing/product analytics—fewer connectors for general-purpose ETL.
- Transformation capabilities are limited to simple mappings; complex needs require additional tools.
- Pricing scales quickly as more sources are connected or higher sync frequency is needed.
Blendo Pricing:
What I like about Blendo
Blendo’s turnkey dashboards and consolidated metrics saved us weeks of manual work—data from all our marketing tools was in BigQuery overnight.
What I dislike about Blendo
Limited customization: can’t define complex transformation logic beyond basic field mappings and date handling.
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.
Feature-by-Feature Comparison
Ease of Use & Interface
Blendo
Blendo’s web UI focuses on connecting predefined sources (select connector, authenticate, choose tables). Once set, data flows automatically on a schedule. Very little configuration needed—ideal for marketers/analysts.
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.
Pricing & Affordability
Blendo
Plans start at $100/month for 1 source, 1 warehouse, and 1 dashboard sync. Higher tiers add connectors and more frequent syncs. Good value for small analytics use cases, but costs increase if you add many sources.
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.
Feature Set
Blendo
Features: SaaS connectors (marketing, CRM, product), incremental sync, metrics layer, pre-built BI dashboards (Data Studio, Looker), monitoring & alerts. Limited to analytics-focused data; no general-purpose ETL features.
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.
Flexibility & Customization
Blendo
Users can define custom SQL transformations on the loaded data via a “SQL runner” feature, but most heavy transformations are done post-load in the warehouse or BI tool. No built-in Python/JS transforms.
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 Blendo vs Mozart Data vs Weld
Weld | Blendo | Mozart Data | |
---|---|---|---|
Connectors | 200+ | 30+ | 150+ |
Price | $79 / No data volume limits | Small plan starts ~$100/month; scales by data volume and connector count | Starts around $1,000/mo (includes Snowflake + ETL up to 250k MAR) |
Free tier | No | Yes | Yes |
Location | EU | Sofia, Bulgaria (HQ) + USA offices | 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 | Yes | 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 | 4.3 | 4.6 |
Conclusion
You’re comparing Blendo, Mozart Data, Weld. Each of these tools has its own strengths:
- Blendo: features: saas connectors (marketing, crm, product), incremental sync, metrics layer, pre-built bi dashboards (data studio, looker), monitoring & alerts. limited to analytics-focused data; no general-purpose etl features. . plans start at $100/month for 1 source, 1 warehouse, and 1 dashboard sync. higher tiers add connectors and more frequent syncs. good value for small analytics use cases, but costs increase if you add many sources. .
- 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..