Based on 144 reviews and ratings
Alooma and Matillion provide data integration capabilities for businesses. Alooma, which was purchased by Google in 2019, provides a more comprehensive platform for integrating applications and systems, as well as data flows, while Matillion specializes as a point solution for data Extraction, Transformation, and Loading (ETL).
Alooma is an Integration Platform as a Service (iPaaS), which entails an architectural foundation for connecting applications and datastreams, in this case with a specialization in integrating data sources with Google’s BigQuery data warehouse. Matillion focuses on extracting data from an original source, or many original sources, formatting the data for the end user, and storing it in a data warehouse.
Alooma and Matillion both have strong features tailored to their corresponding use cases.
Alooma provides features that span a wide range of data integration needs. In particular, Alooma offers mature data mapping capabilities, which grants flexibility when dataflows change and enable non-IT users. It also specializes in loading data into Google’s BigQuery data warehouse.
Matillion’s specialization as an ETL solution allows it to excel in this capacity. Users point to Matillion’s ability to transform data from a wide range of platforms and cloud-based environments. In particular, the product is ideal for integrating AWS applications and data warehouses.
While both products have tailored strengths, each also has tradeoffs and limitations in their offerings.
While Alooma’s transformation and broader ETL capabilities are reliable, they can be overly simplistic. Some users have experienced limitations in the platform’s single-step transformation flow. Since it’s purchase by Google, it is also more limited outside of feeding data to Google’s BigQuery data warehouse.
In contrast, while Matillion specializes in cloud-based ETL into data warehouses, it may be more limited beyond this use case. It lacks some mapping features for non-IT users, and may not offer the same security features for more complex integrations beyond ETL into data warehouses. Some organizations may experience difficulties scaling their instances of the tool as well.
Alooma provides limited pricing information, and exact figures are available by quote from the vendor. Some dated figures place average pricing between $1,000-$1,500 per month to use the service.
Matillion provides four packages for its ETL capabilities, priced per hour of usage. The “Medium” package, at $1.27/hr, provides 2 users and 6 environments. The “Large” package, at $2.74/hr, supports 5 concurrent users and 15 environments and clustering. The “XLarge” package, at $5.48/hr, supports 12 concurrent users and 35 environments. Enterprise package pricing is available by quote from the vendor.
Provided by the TrustRadius Research Team
Published on May 15, 2020
Likelihood to Recommend
Feature Rating Comparison
Support for real-time and batch integration
Data quality services
Data security features
Connect to traditional data sources
Connecto to Big Data and NoSQL
Data model creation
Business rules and workflow
Testing and debugging
Integration with data quality tools
Integration with MDM tools
- Transformation of data before entering the data warehouse -- allows for a consistent/understandable schema for analytics teams.
- Adding of additional data sources: Alooma has a large library of pre-built, common 3rd party vendors for which data is often needed to be ETL-ed.
- The workspace is drag and drop, which makes it intuitive and easy to use.
- Server creation and management is robust. We haven't had to worry too much about it once we got it created.
- The job scheduler is very simple and intuitive.
- Matillion allows you to run Python, which grants almost unlimited flexibility, even without using any other components.
- More tools on managing the data warehouse itself. Although great on the ingest and transformation of data, more help provided by the tool on managing the outputs would be welcome.
- Increase possibilities in the transformation step, rather than single event transformations.
- Limited selection of instance sizes - Larger organizations and groups my need to set up multilple instances depending on estimations on concurrent users.
- Lack of complete github, gitlab, or other source control integration - it has internal versioning but it is limited. Manual job exports currently don't lend well for useful DIFFs comparison when using those technologies.
- Needs more options for authentication and security - User creation is very manual and can be tedious and difficult to manage for larger installations.
Likelihood to Renew
Return on Investment
- Allowing for additional data sources to more automation capability around monitoring the business is a huge ROI
- I was able to build a complete commissions processing system for over 3500 employees using Matillion in just over a month. This included gathering data from 5 different sources, combining them together appropriately and building in the business rules. I was awarded one of the top awards our company gives for this project.
- Our big three Business Intelligence tools: Matillion, Redshift and DOMO allow us to give our employees the right data at the right time. Our productivity has increased as 75%+ of our employees look at their data every day they work.