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.”
Comparing Alooma with CloverDX and Weld
You’re comparing Alooma vs CloverDX vs Weld. Explore how they differ on connectors, pricing, and features. 
Loved by data teams from around the world
Weld vs Alooma vs CloverDX
| Weld | Alooma | CloverDX | |
|---|---|---|---|
| Connectors | 200+ | 100+ | 150+ |
| Price | $99 / 5M Active Rows | N/A (product retired; GCP service pricing applies) | Subscription or perpetual licensing (custom quotes, typically $20k+ annually) |
| Free tier | |||
| Location | EU | Sunnyvale, CA, USA (pre-acquisition) | Culver City, CA, USA |
| Extract data (ETL) | |||
| Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL) | |||
| Transformations | |||
| AI Assistant | |||
| On-Premise | |||
| Orchestration | |||
| Lineage | |||
| Version control | |||
| Load to/from Excel | Yes (Excel/CSV) | ||
| Load to/from Google Sheets | Yes (via API) | ||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | — | 4.2 |
Overview
Alooma in Short
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.
Reviews & Quotes
Google Cloud’s Dataflow (Alooma integration):
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.”
Overview
CloverDX in Short
CloverDX is an enterprise-grade ETL/ELT platform that emphasizes flexibility, automation, and scalability in designing complex data workflows. It supports both code-based and GUI-driven development, making it suitable for both developers and data engineers. It is also known for its transformation, data quality, and data migration capabilities. CloverDX helps to deliver a seamless onboarding process for clients, saving hours of manual work with automated conversion from any file format.
Pros
Metadata-driven: automatic handling of schema drift and impact analysis across pipelines.
Visual Graphical Data Mixer for building data flows, with reusable subgraphs and components.
Supports both batch and streaming ingestion, with connectors to databases, cloud storage, Hadoop, and REST APIs.
Built-in scheduling, monitoring dashboards, alerting, and role-based access control.
Cons
High licensing costs make it less suitable for smaller teams or startups.
Designer IDE can feel heavy and less intuitive for simple tasks; learning curve for new users.
Less community presence than open-source tools, so third-party resources and tutorials are limited.
Reviews & Quotes
Gartner Peer Review:
What I like about CloverDX
“Ability to design elegant data flows and work with really dirty data. The visual design ensures that you write proper rules to deal with a variety of data quality issues”
What I dislike about CloverDX
“Lack of support for AI, Machine learning, Neural networks and ability to run basic regression.”
Overview
Weld in Short
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
Lineage, orchestration, and workflow features
Ability to handle large datasets and near real-time data sync
ETL + reverse ETL in one
User-friendly and easy to set up
Flat monthly pricing model
200+ connectors (Shopify, HubSpot, etc.)
AI assistant
Cons
Requires some technical knowledge around data warehousing and SQL
Limited features for advanced data teams
Focused on cloud data warehouses
Reviews & Quotes
A reviewer on G2 said:
What I like about Weld
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
Feature
Alooma
CloverDX
Weld
Feature
Alooma
CloverDX
Weld
Ease of Use & Interface
Side-by-side
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.
CloverDX
CloverDX Designer is an Eclipse-based IDE where developers build data flow graphs. The drag-and-drop canvas is powerful but can feel cluttered for large projects. Reusable components and parameterization help, but initial learning is significant.
Weld
Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.
Ease of Use & Interface
Side-by-side
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.
CloverDX Designer is an Eclipse-based IDE where developers build data flow graphs. The drag-and-drop canvas is powerful but can feel cluttered for large projects. Reusable components and parameterization help, but initial learning is significant.
Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.
Pricing & Affordability
Side-by-side
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.
CloverDX
CloverDX’s pricing is tiered by job servers, connector count, and features—often starting around $20k/year. Best for medium-to-large organizations requiring robust metadata handling and enterprise governance.
Weld
Weld offers a straightforward and competitive pricing model, starting at $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises.
Pricing & Affordability
Side-by-side
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.
CloverDX’s pricing is tiered by job servers, connector count, and features—often starting around $20k/year. Best for medium-to-large organizations requiring robust metadata handling and enterprise governance.
Weld offers a straightforward and competitive pricing model, starting at $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises.
Feature Set
Side-by-side
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.
CloverDX
Features include: visual data flow designer, metadata-driven transformations, automated schema evolution, batch & streaming support, job scheduling & monitoring, role-based access, and REST/JSON/XML connectors. Also offers advanced data quality and permutation-based testing.
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.
Feature Set
Side-by-side
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.
Features include: visual data flow designer, metadata-driven transformations, automated schema evolution, batch & streaming support, job scheduling & monitoring, role-based access, and REST/JSON/XML connectors. Also offers advanced data quality and permutation-based testing.
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.
Flexibility & Customization
Side-by-side
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.
CloverDX
Users can develop custom Java or Groovy components for specialized transformations, extend connectors via REST templates, and integrate with external schedulers. The open API allows embedding Clover DX in other applications.
Weld
Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.
Flexibility & Customization
Side-by-side
Users could write custom JavaScript transforms or Python UDFs for complex logic. The platform managed infrastructure, but custom connectors required Eloqua code or support.
Users can develop custom Java or Groovy components for specialized transformations, extend connectors via REST templates, and integrate with external schedulers. The open API allows embedding Clover DX in other applications.
Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.
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