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Comparing Alooma with Jitterbit and Weld

You’re comparing Alooma vs Jitterbit vs Weld. Explore how they differ on connectors, pricing, and features. Ed Logo

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Weld vs Alooma vs Jitterbit

WeldAloomaJitterbit
Connectors200+100+100+
Price$99 / 5M Active RowsN/A (product retired; GCP service pricing applies)Subscription-based (custom quotes; starts ~$25k/year)
Free tier
LocationEUSunnyvale, CA, USA (pre-acquisition)Oakland, 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 ExcelYes (via Excel connector)
Load to/from Google Sheets
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating4.84.3

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.

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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 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.

Overview

Jitterbit in Short

Jitterbit Harmony is a cloud-based integration platform that supports ETL, API integration, and application connectivity. Its core concept is “Harmony Cloud Integration,” where users design “Jitterpaks” (integration packages) via a visual interface. Jitterbit offers pre-built connectors to major SaaS apps (Salesforce, NetSuite), on-prem databases, and flat files. It also supports real-time API creation from data sources and transformation using SQL or scripting.

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Pros

  • Pre-built connectors for CRM, ERP, databases, and flat files; plus the ability to build custom connectors via SDK.

  • API creation feature: turn data flows into REST or SOAP endpoints on the fly.

  • Visual Studio for designing Jitterpaks (pipelines), with drag-and-drop mapping and transformation steps.

  • Real-time and batch modes supported; can deploy on Jitterbit’s cloud or your own servers (hybrid).

Cons

  • Complex licensing (based on endpoints, environments, and usage) can be expensive for heavy data volumes.

  • Studio interface can feel less modern compared to newer iPaaS; large, complex flows can become unwieldy.

  • Some advanced transformations require writing custom code rather than purely using GUI.

Reviews & Quotes

Jitterbit Harmony Overview:

What I like about Jitterbit

Jitterbit’s Studio UI makes building integrations straightforward, and the API creation feature lets us expose data to external apps quickly.

What I dislike about Jitterbit

Pricing is tiered and can be high as you add more endpoints or data volume. Complex transformations sometimes require scripting, despite the low-code interface.

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.

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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

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

Feature
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Alooma

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Jitterbit

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Weld

Ease of Use & Interface

Side-by-side

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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.

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Jitterbit

Jitterbit’s Studio is a Java-based desktop application (also has a web version) with a canvas for designing operations. It supports mapping between schemas, scripting for complex logic, and testing within the UI. Some users find it less responsive for very large flows.

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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.

Pricing & Affordability

Side-by-side

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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.

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Jitterbit

Pricing depends on number of endpoints, environments (dev/test/prod), and data volume. Smaller teams might start around $25k/year, but enterprise usage can cost significantly more.

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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.

Feature Set

Side-by-side

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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.

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Jitterbit

Features include: ETL/ELT pipelines, API generation, cloud & on-prem deployment, real-time event triggers, pre-built templates (“Jitterpaks”), and monitoring dashboards. Also supports multi-environment promotion and CI/CD.

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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.

Flexibility & Customization

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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.

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Jitterbit

Users can embed JavaScript or VBScript for transformations. Jitterbit’s SDK allows building custom connectors. While hybrid deployment is possible, full feature access often requires cloud usage.

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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.

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