Comparing Alooma with Matillion and Weld
Carolina Russ5 min read
What is Alooma
Alooma (acquired by Google Cloud in 2019) was a streaming ETL platform that enabled real-time ingestion of data from various sources into BigQuery. It provided a visual pipeline editor to map, transform, and route data with minimal code, automatically handling schema changes and ensuring exactly-once delivery. While Alooma as a standalone product is retired, many of its features have been integrated into Google Cloud’s Dataflow and Pub/Sub pipelines.
Pros
- Real-time streaming ETL with automatic schema drift handling.
- Minimal coding: visual pipeline UI with built-in connectors to databases, Kafka, APIs, and SaaS apps.
- Exactly-once delivery guarantees to BigQuery, eliminating duplicate data.
Cons
- Standalone Alooma product is discontinued—functionality now lives in GCP services (e.g., Dataflow, Data Fusion).
- Migrating legacy Alooma pipelines to GCP-native services requires rework, as UI and features differ from original Alooma.
Google Cloud’s Dataflow (Alooma integration):
What I like about Alooma
Alooma’s ease of connecting live streaming data sources directly into BigQuery with automated schema management was revolutionary for our real-time analytics.
What I dislike about Alooma
Since Google integrated Alooma into its native services, the standalone product no longer exists, so new users must migrate to Dataflow or Data Fusion.
What is Matillion
Matillion is a well-established data processing engine that offers advanced ETL/ELT and data transformation processes for larger enterprises.
Pros
- Large number of connectors
- Robust feature set
- Lots of advanced features for larger enterprises and data teams
- Has both ELT and ETL capabilities
- On premise options
Cons
- Expensive for small businesses
- Steep learning curve for non-technical users
- Requires a large upfront investment and implementation
As a reviewer on Gartner puts it: :
What I like about Matillion
Matillion ETL Platform Enables Robust Data Pipelines Without Constraints
What I dislike about Matillion
What is Weld
Weld is a powerful ETL platform that seamlessly integrates ELT, data transformations, reverse ETL, and AI-assisted features into one user-friendly solution. With its intuitive interface, Weld makes it easy for anyone, regardless of technical expertise, to build and manage data workflows. Known for its premium quality connectors, all built in-house, Weld ensures the highest quality and reliability for its users. It is designed to handle large datasets with near real-time data synchronization, making it ideal for modern data teams that require robust and efficient data integration solutions. Weld also leverages AI to automate repetitive tasks, optimize workflows, and enhance data transformation capabilities, ensuring maximum efficiency and productivity. Users can combine data from a wide variety of sources, including marketing platforms, CRMs, e-commerce platforms like Shopify, APIs, databases, Excel, Google Sheets, and more, providing a single source of truth for all their data.
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.
Alooma vs Matillion: Ease of Use and User Interface
Alooma
Alooma’s web-based pipeline builder allowed users to drag-and-drop connectors for streaming or batch data, apply transformations, and route data to BigQuery with just a few clicks. The interface auto-generated SQL when possible.
Matillion
Matillion has a steep learning curve, especially for non-technical users, due to its robust feature set and advanced capabilities designed for larger enterprises.
Alooma vs Matillion: Pricing Transparency and Affordability
Alooma
No longer available as a separate product. Users adopt equivalent GCP services (Dataflow, Data Fusion) which have pay-as-you-go pricing under the GCP pricing model.
Matillion
Matillion's pricing can be expensive, particularly for small businesses, as it is based on credits and requires a significant upfront investment.
Alooma vs Matillion: Comprehensive Feature Set
Alooma
Alooma supported real-time ingestion from Kafka, databases (MySQL, PostgreSQL), logs, REST APIs, and SaaS apps, with built-in transformations (masking, enrichment). It automatically handled schema changes, and could write to BigQuery partitions.
Matillion
Matillion offers a robust set of features with support for both ETL and ELT, along with numerous connectors and on-premise options, making it ideal for large enterprises with complex data needs.
Alooma vs Matillion: Flexibility and Customization
Alooma
Users could write custom JavaScript transforms or Python UDFs for complex logic. The platform managed infrastructure, but custom connectors required Eloqua code or support.
Matillion
Matillion provides extensive customization and flexibility options, particularly for large enterprises, but may be overkill for smaller teams or simpler use cases.
Summary of Alooma vs Matillion vs Weld
| Weld | Alooma | Matillion | |
|---|---|---|---|
| Connectors | 200++ | 100+ | 110+ |
| Price | $99 / Unlimited usage | N/A (product retired; GCP service pricing applies) | $2.00 per credit |
| Free tier | No | No | Yes |
| Location | EU | Sunnyvale, CA, USA (pre-acquisition) | UK |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | Yes |
| Transformations | Yes | Yes | Yes |
| AI Assistant | Yes | No | No |
| On-Premise | No | No | Yes |
| Orchestration | Yes | Yes | Yes |
| Lineage | Yes | No | No |
| Version control | Yes | No | No |
| Load data to and from Excel | Yes | No | No |
| Load data to and from Google Sheets | Yes | No | No |
| Two-Way Sync | Yes | No | No |
| dbt Core Integration | Yes | No | No |
| dbt Cloud Integration | Yes | No | No |
| OpenAPI / Developer API | Yes | No | Yes |
| G2 Rating | 4.8 | 4.3 |
Conclusion
You’re comparing Alooma, Matillion, Weld. Each of these tools has its own strengths:
- Alooma: alooma supported real-time ingestion from kafka, databases (mysql, postgresql), logs, rest apis, and saas apps, with built-in transformations (masking, enrichment). it automatically handled schema changes, and could write to bigquery partitions. . no longer available as a separate product. users adopt equivalent gcp services (dataflow, data fusion) which have pay-as-you-go pricing under the gcp pricing model. .
- Matillion: matillion offers a robust set of features with support for both etl and elt, along with numerous connectors and on-premise options, making it ideal for large enterprises with complex data needs.. matillion's pricing can be expensive, particularly for small businesses, as it is based on credits and requires a significant upfront investment..
- 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..
