Alooma vs. Matillion

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Alooma
Score 9.0 out of 10
N/A
Alooma is a data integration product providing ETL capabilities with a focus on output to data warehouse. It also offers pipeline monitoring and error handling protocols.N/A
Matillion
Score 6.3 out of 10
N/A
Matillion is a productivity platform for data teams. Matillion's Data Productivity Cloud helps data teams – coders and non-coders alike – to move, transform, and orchestrate data pipelines with the goal of empowering teams to deliver quality data at a speed and scale that matches the business’s data ambitions. The vendor states enterprises including Cisco,N/A
Pricing
AloomaMatillion
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
AloomaMatillion
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsBilled directly via cloud marketplace on an hourly basis, with annual subscriptions available depending on the customer's cloud data warehouse provider.
More Pricing Information
Community Pulse
AloomaMatillion
Considered Both Products
Alooma

No answer on this topic

Matillion
Chose Matillion
If you take the time to build your own with Matillion, you will end up with a vastly better solution than Stitch and Fivetran. We ran Stitch and Fivetran side by side connected from our source DB to both RedShift and Snowflake and documented the performance results as well as …
Chose Matillion
Matillion provided much more flexibility than the other products we tested, at a much lower price point. Other products, in my view, had a cleaner/simpler UI but I also felt that they offered much less functionality. A key design pattern we had to deliver was to perform delta …
Chose Matillion
Matillion had out of the box support for most of the third party tools we have, plus it integrates well with our data warehouse platform. We found it to meet our use cases after a trial period. It's customizable when you know what you are doing. The use of global and local …
Chose Matillion
There's a number of systems not available to enter in here that we also took a look at: AWS Data pipeline, Airflow, Xplenty, etc. The reason we chose Matillion is for the balance of features (ability to connect into cloud data sources like Jira), a simple interface to put …
Chose Matillion
Matillion is the best alternative for on-premise ETL tools if you are looking for a cloud-only solution. None of the tools we evaluated provide same features offered by Matillion. Extensive technical documentation is available on the website which makes development easy and …
Chose Matillion
Generally, Matillion is much easier to get up and running, quicker to deliver value and returns on your ELT process, and simpler to maintain. The speed to get data connections and start pulling data is so quick that you can focus on the transformations and business rules …
Chose Matillion
Our organization hires present college students in an apprenticeship role, so it was important to us that whatever tool we use to be easy to train on. We also preferred that it integrate well with Snowflake since we had decided that we wanted to use that as our data storage …
Chose Matillion
Matillion gave us more flexibility for our purposes, and we didn't have to program a lot in Python or any other programming language to transform the data. With Matillion we could implement our metadata-driven approach and we had everything in one tool. New developers can …
Top Pros
Top Cons
TrustRadius Insights
AloomaMatillion
Highlights

TrustRadius
Research Team Insight
Published

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.  

Features 

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. 

Limitations 

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. 

Pricing

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. 

Features
AloomaMatillion
Cloud Data Integration
Comparison of Cloud Data Integration features of Product A and Product B
Alooma
7.5
1 Ratings
8% below category average
Matillion
-
Ratings
Pre-built connectors8.01 Ratings00 Ratings
Connector modification7.01 Ratings00 Ratings
Support for real-time and batch integration7.01 Ratings00 Ratings
Data quality services8.01 Ratings00 Ratings
Data security features7.01 Ratings00 Ratings
Monitoring console8.01 Ratings00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Alooma
-
Ratings
Matillion
7.3
126 Ratings
13% below category average
Connect to traditional data sources00 Ratings7.5125 Ratings
Connecto to Big Data and NoSQL00 Ratings7.085 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Alooma
-
Ratings
Matillion
6.1
127 Ratings
30% below category average
Simple transformations00 Ratings6.7127 Ratings
Complex transformations00 Ratings5.5126 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Alooma
-
Ratings
Matillion
6.9
119 Ratings
15% below category average
Data model creation00 Ratings9.133 Ratings
Metadata management00 Ratings9.140 Ratings
Business rules and workflow00 Ratings6.2111 Ratings
Collaboration00 Ratings4.0111 Ratings
Testing and debugging00 Ratings4.6112 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Alooma
-
Ratings
Matillion
8.2
23 Ratings
1% below category average
Integration with data quality tools00 Ratings8.222 Ratings
Integration with MDM tools00 Ratings8.220 Ratings
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User Ratings
AloomaMatillion
Likelihood to Recommend
8.0
(1 ratings)
6.2
(128 ratings)
Likelihood to Renew
-
(0 ratings)
8.3
(6 ratings)
Usability
-
(0 ratings)
5.4
(127 ratings)
Support Rating
-
(0 ratings)
7.4
(7 ratings)
Implementation Rating
-
(0 ratings)
8.2
(1 ratings)
Product Scalability
-
(0 ratings)
5.3
(120 ratings)
Vendor post-sale
-
(0 ratings)
9.1
(1 ratings)
Vendor pre-sale
-
(0 ratings)
9.1
(1 ratings)
User Testimonials
AloomaMatillion
Likelihood to Recommend
Alooma
Very appropriate for managing an ELT stack -- Alooma handles the 'E' and 'L' pieces very well. Due to the way transformation is setup, it is more on the lightweight side of things and thus works for this kind of stack. For more traditional ETL stacks, Alooma would probably not be the right fit.
Read full review
Matillion
Matillion is very easy to learn and develop quickly. It also allows complex orchestration on a visual platform. It has many ready-made components, and it is easy to develop new user components. Although Git integration needs some further development, it enables teamwork in the same project with the "Versions."
Read full review
Pros
Alooma
  • 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.
Read full review
Matillion
  • Matillion has a rich transformation library. It provides multiple functionalities, such as join, group by, pivot, various sources, and sinks.
  • It provides the security capability as well. All the credentials can be securely stored in Matillion.
  • Reusable templates can be built which reduces the redundancy.
  • Time to production is very minimal.
Read full review
Cons
Alooma
  • 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.
Read full review
Matillion
  • Static and monolithic, it will show its limits when running multiple concurrent jobs.
  • Github and versioning implementation is messy and broken. Don't use it.
  • There's not way to see/query the system resources, just wait for a server to crash due to out of memory. An admin panel would be appreciated + some env variables with updated info.
  • API implementation is cumbersome and limited.
  • There's no concept of hub and worker engine, everything happens of the same server (designing workflows and executing them). Having separate light ETL engines to run job could be better. (sort of docker/kubernetes/lambda functions).
  • Handling of variables is limited especially for returned values from sub components.
  • Some components could return more metadata at the end of their execution instead of the standard one.
  • Billing is badly designed not taking into account that the server is hosted by the client. Expensive.
  • We had several issue with migration where starting a new instance was required and then migrating the content. It was painful and time consuming also have to deal with support and engineering team on Matillion side.
  • CDC doesn't work as expected or it is not a mature product yet.
Read full review
Likelihood to Renew
Alooma
No answers on this topic
Matillion
With the current experience of Matillion, we are likely to renew with the current feature option but will also look for improvement in various areas including scalability and dependability. 1. Connectors: It offers various connectors option but isn't full proof which we will be looking forward as we grow. 2. Scalability: As usage increase, we want Matillion system to be more stable.
Read full review
Usability
Alooma
No answers on this topic
Matillion
Data modeling and SQL knowledge are still heavily recommended when using Matillion because designing a successful and maintainable data transformation requires modeling it with a developer mindset. The data transformation components are often a thin wrapper around SQL concepts, and they don't simplify life that much, IMO. An example is the window component, which cannot facilitate the complex concept of SQL windows just by exposing it to a different interface. On the other hand, low code ingestion is very good and usable, especially for GSheets, Salesforce, and others.
Read full review
Support Rating
Alooma
No answers on this topic
Matillion
Overall, I've found Matillion to be responsive and considerate. I feel like they value us as a customer even when I know they have customers who spend more on the product than we do. That speaks to a motive higher than money. They want to make a good product and a good experience for their customers. If I have any complaint, it's that support sometimes feels community-oriented. It isn't always immediately clear to me that my support requests are going to a support engineer and not to the community at large. Usually, though, after a bit of conversation, it's clear that Matillion is watching and responding. And responses are generally quick in coming.
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Implementation Rating
Alooma
No answers on this topic
Matillion
We were able to control on access and built various enviroment for implementation
Read full review
Alternatives Considered
Alooma
Haven't used the alternatives, since Alooma was one of the earlier ones to the market. From a cursory viewing, however, the features seem to match relatively similarly.
Read full review
Matillion
Matillion is much easier to set up and easier to work for the team. Offers a lot more connections which are easier to set up. Environment variables make it easy to set up once and job creation is easy. We use Metadata tables to just loop through the list of tables that need to be loaded. So development is just a matter of seconds when there are new tables to be loaded.
Read full review
Scalability
Alooma
No answers on this topic
Matillion
The current connectivity is set to provide information primarily in one direction; from simpler OLTP systems to big data warehouses. Allowing the big data warehouses (e.g., Snowflake) to be used as a source for transmission elsewhere would be a big extension to the product line and provide more flexibility in architecture.
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Return on Investment
Alooma
  • Allowing for additional data sources to more automation capability around monitoring the business is a huge ROI
Read full review
Matillion
  • Our embedded data analysts (data analysts that sit in a team outside of the Data team) all now use Matillion to create proof of concepts (POCs). This allows them to debug logic at a component level and quickly explore ideas without investing lots of time and effort.
  • Since the soft-announcement of ‘Data as a product’ (a beta launch) and demoing Matillion to some of our internal customers we’ve had a huge number of requests from people to get their hands on this new method of self serving data. We’ve yet to release the full product and make a company wide announcement, but early estimates show we can expect around 10-15% of the company to be onboarded and using Matillion as part of Data as a Product. Given the Data team only accounts for around 2% for the company's employees, that’s a huge increase in the number of people using and manipulating raw data!
Read full review
ScreenShots

Matillion Screenshots

Screenshot of Matillion's GUI, used to orchestrate jobs with control data flow functionality, automating the ETL process.Screenshot of where structured and semi-structured data can be prepared to create clean data sets that can be used with any BI/reporting/visualization tool of choice. Matillion reads and combines data across a target warehouse external storage, such as S3 or Blob.Screenshot of Matillion's self-validating components, sample and row counts. If a job does fail, the warehouse queue services available with Matillion can be used get an alert to a connected email or Slack account.Screenshot of the SQL component used to run custom scripts from within Matillion. With hundreds of pre-built connectors out of the box, Matillion can handle complex transformation needs.