Comparing Alooma with Databox 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 Databox
Databox is a cloud-based data visualization and business intelligence platform that helps businesses of all sizes track, analyze, and share their key performance indicators (KPIs). It offers a wide range of features, including the ability to connect to multiple data sources, create custom dashboards, and share insights with others.
Pros
- Easy to use
- Powerful features
- Great customer support
- Comprehensive data visualization
- Real-time data updates
Cons
- Expensive
- Limited customization
- Lack of advanced features
- Limited drill-down capabilities
A reviewer on Capterra:
What I like about Databox
Databox is always looking for ways to improve its interface. It's smooth - data updates quickly and it's easy to use. The customer service is super responsive, and always willing to step in and help out with the Databoards (dashboards) I'm working on. I would say it is my favorite tool to use as an analyst - ever!
What I dislike about Databox
Still missing some more obscure, less popular, integrations.
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 Databox: 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.
Databox
Databox is easy to use with a smooth interface and real-time data updates, making it a favorite among analysts for data visualization and reporting.
Alooma vs Databox: 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.
Databox
Databox is on the pricier side, which might deter smaller businesses or startups with limited budgets, despite its robust features and customer support.
Alooma vs Databox: 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.
Databox
The platform offers powerful data visualization tools and comprehensive dashboards, but lacks advanced features and customization options, which could be limiting for some users.
Alooma vs Databox: 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.
Databox
Databox provides a range of data visualization tools, but customization is limited, particularly for more complex reporting and analysis needs.
Summary of Alooma vs Databox vs Weld
| Weld | Alooma | Databox | |
|---|---|---|---|
| Connectors | 200++ | 100+ | 100+ |
| Price | $99 / Unlimited usage | N/A (product retired; GCP service pricing applies) | $47 / month - 3 sources, 5 users |
| Free tier | No | No | Yes |
| Location | EU | Sunnyvale, CA, USA (pre-acquisition) | US |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
| Transformations | Yes | Yes | No |
| AI Assistant | Yes | No | No |
| On-Premise | No | No | No |
| Orchestration | Yes | Yes | No |
| 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 | No |
| G2 Rating | 4.8 | 4.5 |
Conclusion
You’re comparing Alooma, Databox, 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. .
- Databox: the platform offers powerful data visualization tools and comprehensive dashboards, but lacks advanced features and customization options, which could be limiting for some users.. databox is on the pricier side, which might deter smaller businesses or startups with limited budgets, despite its robust features and customer support..
- 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..
