Comparing Alooma with Qlik Replicate and Weld
Carolina Russ6 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 Qlik Replicate
Qlik Replicate (formerly Attunity) is a change data capture (CDC) and replication platform that moves data in real-time from databases, mainframes, and cloud sources into data warehouses, data lakes, and analytics platforms. It provides a graphical UI to configure replication tasks, automated schema change handling, and supports a wide range of sources (Oracle, SQL Server, DB2, MongoDB) and targets (Snowflake, Redshift, BigQuery, Kafka).
Pros
- High-performance CDC with minimal source impact; supports heterogeneous sources and targets.
- Automated schema change handling—table/column additions in source auto-reflected in target.
- GUI-based configuration for tasks, monitoring dashboards, and robust error handling.
- Cloud-native or on-prem installations; integrates with Qlik’s broader ecosystem (e.g., Qlik Sense).
Cons
- No built-in ELT/transformations—only replication. Users need a separate tool for data transformations.
- Enterprise pricing (per-core licensing) can be high, particularly for large-scale replication across many tables.
- Learning curve for setting up advanced replication scenarios (e.g., multi-target replication, filters).
Qlik Replicate Documentation:
What I like about Qlik Replicate
Replicate’s CDC capabilities ensure minimal latency and zero-impact on source databases. Schema changes in the source are automatically captured and propagated to targets.
What I dislike about Qlik Replicate
Licensing is expensive, and it’s focused solely on replication (no transformations). For broader ETL, additional tools are needed.
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.
Feature-by-Feature Comparison
Ease of Use & 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.
Qlik Replicate
The Qlik Replicate UI provides wizards to create replication tasks quickly, monitors latency and throughput, and auto-detects schema changes. Setup for common CDC tasks is straightforward, but advanced filtering and tuning require expertise.
Pricing & 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.
Qlik Replicate
The licensing model is per-engine/core, often starting at $50k+/year for smaller environments. While expensive, the high reliability and low-latency replication justify cost for mission-critical use cases.
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.
Qlik Replicate
Features: CDC-based replication, automated schema drift handling, support for 100+ sources/targets (databases, mainframes, cloud), multi-target replication, and basic transformations (e.g., data type conversions). No deep transformation engine.
Flexibility & 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.
Qlik Replicate
Users can configure advanced mapping rules, filters, and transformations (limited) via the UI or JSON configs. For deeper transforms, integrate with Qlik Compose or third-party ETL. Qlik Replicate can be automated via CLI and REST API.
Summary of Alooma vs Qlik Replicate vs Weld
| Weld | Alooma | Qlik Replicate | |
|---|---|---|---|
| Connectors | 200+ | 100+ | 100+ |
| Price | $79 / No data volume limits | N/A (product retired; GCP service pricing applies) | Subscription/perpetual license (custom quotes; six-figure enterprise costs) |
| Free tier | No | No | No |
| Location | EU | Sunnyvale, CA, USA (pre-acquisition) | King of Prussia, PA, USA (Qlik HQ) |
| Extract data (ETL) | Yes | Yes | No |
| 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 | 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 | 4.7 |
Conclusion
You’re comparing Alooma, Qlik Replicate, 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. .
- Qlik Replicate: features: cdc-based replication, automated schema drift handling, support for 100+ sources/targets (databases, mainframes, cloud), multi-target replication, and basic transformations (e.g., data type conversions). no deep transformation engine. . the licensing model is per-engine/core, often starting at $50k+/year for smaller environments. while expensive, the high reliability and low-latency replication justify cost for mission-critical use cases. .
- 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..
