Comparing Mozart Data with Pentaho Data Integration and 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 Pentaho Data Integration
Pros
- Open-source (Community Edition) with no licensing costs; Enterprise Edition provides additional features and support.
- 150+ connectors (databases, cloud storage, big data, files, NoSQL) and flexible step-based transformations.
- Graphical Spoon interface for visual ETL job design; transformations can be previewed and tested in real-time.
- Support for clustered execution (Carte server) for parallel processing and higher throughput.
Cons
- Community Edition lacks advanced features (lineage, data quality, enterprise monitoring), requiring Enterprise Edition for production readiness.
- Performance can suffer with very large data volumes if not properly tuned (Java memory, clustering).
- User interface and user experience are dated compared to newer cloud-native ETL tools.
Pentaho Data Integration Overview:
What I like about Pentaho Data Integration
PDI’s free community edition and Spoon GUI allow rapid ETL prototyping; its step library is extensive, and clustering support is solid for scale.
What I dislike about Pentaho Data Integration
Limited data quality features and slower development speed compared to modern cloud ETL. Community support can be slow for fixes.
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
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.
Pentaho Data Integration
Pentaho’s Spoon GUI uses a canvas paradigm: drag "steps" onto a transformation, connect them, and configure. While powerful, it can feel clunky, especially for very complex flows with many steps.
Pricing & 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.
Pentaho Data Integration
The free Community Edition is attractive for experimentation. Enterprise Edition pricing is usage-based and includes support, lineag, and more; typically suited for mid-sized to large organizations.
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.
Pentaho Data Integration
PDI features: GUI-based transformation designer, job orchestration, data cleansing, lookups, joins, scripting (JavaScript, PDI’s built-in “User Defined Java Expression”), logging, clustering, and integration with Pentaho BI for reporting. Lineage and monitoring in Enterprise.
Flexibility & 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.
Pentaho Data Integration
Users can embed Java, JavaScript, or invoke external scripts. PDI’s open architecture allows custom plugins for new steps/connectors. The code is open-source, so full extensibility is available, though it requires Java development.
Summary of Mozart Data vs Pentaho Data Integration vs Weld
Weld | Mozart Data | Pentaho Data Integration | |
---|---|---|---|
Connectors | 200+ | 150+ | 150+ |
Price | $79 / No data volume limits | Starts around $1,000/mo (includes Snowflake + ETL up to 250k MAR) | Community Edition: Free; Enterprise Edition: Custom pricing |
Free tier | No | Yes | Yes |
Location | EU | San Francisco, CA, USA | Santa Clara, CA, USA (Hitachi Vantara HQ) |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
Transformations | Yes | Yes | Yes |
AI Assistant | Yes | No | No |
On-Premise | No | No | Yes |
Orchestration | Yes | Yes | Yes |
Lineage | Yes | No | Yes |
Version control | Yes | No | Yes |
Load data to and from Excel | Yes | Yes | Yes |
Load data to and from Google Sheets | Yes | Yes | Yes |
Two-Way Sync | Yes | No | No |
dbt Core Integration | Yes | Yes | No |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | No | No |
G2 Rating | 4.8 | 4.6 | 4.1 |
Conclusion
You’re comparing Mozart Data, Pentaho Data Integration, Weld. Each of these tools has its own strengths:
- 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. .
- Pentaho Data Integration: pdi features: gui-based transformation designer, job orchestration, data cleansing, lookups, joins, scripting (javascript, pdi’s built-in “user defined java expression”), logging, clustering, and integration with pentaho bi for reporting. lineage and monitoring in enterprise. . the free community edition is attractive for experimentation. enterprise edition pricing is usage-based and includes support, lineag, and more; typically suited for mid-sized to large organizations. .
- 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..