Matillion is a data pipeline platform used to build and manage pipelines. Matillion empowers data teams with no-code and AI capabilities to be more productive, integrating data wherever it lives and delivering data that’s ready for AI and analytics.
$2.50
Pay as you go per user
Talend Data Integration
Score 10.0 out of 10
N/A
The Talend Integration Suite, from Talend, is a set of tools for data integration.
N/A
Pricing
Matillion
Talend Data Integration
Editions & Modules
Developer: For Individuals
$2.50/credit
Pay as you go per user
Basic
$1000
per month 500 prepaid credits (additional credits: $2.18/credit)
Advanced
$2000
per month 750 prepaid credits (additional credits: $2.73/credit)
Enterprise
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Offerings
Pricing Offerings
Matillion
Talend Data Integration
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Billed directly via cloud marketplace on an hourly basis, with annual subscriptions available depending on the customer's cloud data warehouse provider.
Matillion is cheaper and we really like the customer support of Matillion as well as lerning materials provided by Matillion were far better. They also made connectors for us for free while others were charging us for it.
Matillion gives great ability to connect to variety of sources and bring data into cloud data warehouse using connector based approach with which we can build complex transformation jobs which can do automated data fetches from your sources.
Matillion has better capabilities and better built-in elements that saves your time and efforts. also the connectivity across multiple data warehousing tool is better in Matillion. even the performance of the pipeline and the time required to create a particular pipeline is …
My manager selected Million based on his previous work experience. He believes it is easy to use and maintain, cheaper than competitors, and suitable for our use case.
The only other ETL tool I've used was SSIS. At first I thought Matillion seemed "kiddish" after using the polished Microsoft tool but now I think Matillion is easier and can do much more as it has so many built-in connectors etc. We selected Matillion at our job because of …
n/a -- joined the team after they already were established in Matillion. Have had brief looks at other ETL products but found nothing compelling enough to suggest a change.
We selected Matillion primarily because of it's ability to connect to numerous data sources and easily create transformation jobs. While FiveTran does a better job managing and examining deltas, it is not easy to use and is very non user friendly. SSIS was not a good fit for …
Fivetran offers a managed service and pre-configured schemas/models for data loading, which means much less administrative work for initial setup and ongoing maintenance. But it comes at a much higher price tag. So, knowing where your sweet spot is in the build vs. buy spectrum …
We decided to move forward with Matillion because it was the best tool among tools that support both ingesting data from a source system to a target database and running transformation workflows on it afterwards. Fivetran and Airbyte only support data ingestion and we had our …
Cost and ease of use were better for our purposes. Matillion distinguishes itself from Fivetran and Snaplogic through its user-friendly design, no-code interface, in-depth transformation capabilities, allowing for complex data manipulations directly within the platform, …
The Matillion selection was not my decision. But I think it's a good enough choice. It is especially valuable that the team can learn Matillion easily and that the project can be understood by the entire team with the visual environment instead of complex ETLs.
Both the Databricks platform and Dbt Cloud are more powerful from the point of view of the development lifecycle and data use cases covered. They are also more complex and require specialized data engineering skills to be used. Matillion has a lower barrier of entry for small …
Removes most of the complexity around setting up and preparing things. If you could describe with words what needs to be done to move data from A to B, the implementation in Matillion would probably be the most similar in terms of simplicity of understanding what you are doing …
Matillion is a good tool for integrating multiple clouds. Informatica has been a market standard for many years, it provides multiple capabilities for data governance, data quality, etc. However, Informatica is pretty expensive compared to Matillion. Also, Matillion is more …
Talend has many built-in components that reduce the development work. We were able to complete the project sooner than expected. Easy to on-board resources as it is straightforward to use. We can manage all the pipelines in the cloud with simple alerting. No major downtimes. …
In comparison with the other ETLs I used, Talend is more flexible than Data Services (where you cannot create complex commands). It is similar to Datastage speaking about commands and interfaces. It is more user-friendly than ODI, which has a metadata point of view on its own, …
SAP Business Object Data Services is another ETL offering that I have used before Talend. The biggest advantage is that Talend is open source and very user-friendly. SAP BODS needs to improve on the user interface. Also, it works well with relational databases but is not very …
Data Preparation is something which can improved and connectivity with more visualization tools are few factors which can be improved. As Talend Data Integration becomes more cloud focused, the gap in features / functionality widens between on-premise functionality and the …
Talend is the best for ETL out of all the other products we looked at. Of course, it is not meant for synchronous services. But, batch jobs that we schedule and run on bulk data are the best fit for Talend Data Integration. Though Talend does not provide a preview of …
Most other tools of similar nature work well for small and medium sized data warehouses, but fail to maintain performance for very large data warehouses. However, Talend works decently well on large data as well. On the other hand, there are software tools like Oracle Data …
Talend is much versatile in assimilating various different business use cases. It covers more functionality and is packed with tons of features to explore. It has the ability to fine tune to each project, and not be a one-fits all solution. Problems with Excel, is that it is …
There are code building and code conversions internally in most of these ETL tools. The repository is an overhead in the ETL process. There may be a need for a full-time administrator to manage deployments and monitor jobs. With Talend, it seems to be transparent with the pure …
Compared to Microsoft SQL Server Integration Services (SSIS) talend gives developers much more tools and flexibility in order to achieve different ETL processes. For instance, SSIS, separates processing from data management, and Talend mixes both stages so that you can perform …
Talend has all the data integration features needed for an enterprise along with big data integration. It stands tall as a data integration suite and has a low cost as compared to some of its commercial counterparts. Talend does not have reporting tools like Pentaho but its …
Matillion and Talend Data Integration are both data integration tools. Matillion specializes in ETL for cloud-based warehouses. Talend differentiates by offering a free open source version of its data integration platform. Talend is more commonly used at the enterprise level, with a larger focus on big data integration, while Matillion’s cloud focus is gives it functionality across company sizes.
Features
Both Matillion and Talend provide a variety of features for data integration.
Matillion offers a robust Extraction, Transformation, and Loading (ETL) capability. Users highlight its ability to centralize and structure data from a wide range of platforms and cloud environments, particularly AWS applications. Matillion’s focus on cloud-based data warehouses makes it ideal for this use case.
Talend differentiates with its free open source data quality management and integration software, which can be used for simple use cases. At larger scale, Talend also provides a high degree of customizable connectors between different system, including custom-built connectors.
Limitations
Talent and Matillion also both have some limitations to their offerings.
Matillion’s users have struggled to create and utilize the platform’s documentation for updates and project management. This issue is particularly pronounced when implementing or integrating Git.
Talend’s free version is extremely limited for most users. Many ETL tasks quickly scale beyond the technical functionality of the free version, requiring paid upgrades. Talend also struggles with utilizing Git, particularly in the free version of the software.
Pricing
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.
Talend offers four products around data integration. Data Quality and Data Integration are available in open source versions. There are also Data Integration Entry Level and a Data Management Platform package. The former includes more advanced integration features, and the Data Management Platform includes advanced data profiling and quality governance. Pricing is available by quote from the vendor.
Features
Matillion
Talend Data Integration
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Matillion
8.3
Ratings
1% below category average
Talend Data Integration
9.5
Ratings
12% above category average
Connect to traditional data sources
8.70 Ratings
10.00 Ratings
Connecto to Big Data and NoSQL
7.90 Ratings
9.00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Matillion
6.9
Ratings
17% below category average
Talend Data Integration
9.0
Ratings
10% above category average
Simple transformations
7.50 Ratings
9.00 Ratings
Complex transformations
6.40 Ratings
9.00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Matillion
8.2
Ratings
3% above category average
Talend Data Integration
9.0
Ratings
12% above category average
Data model creation
9.10 Ratings
9.00 Ratings
Metadata management
9.10 Ratings
10.00 Ratings
Business rules and workflow
8.30 Ratings
8.00 Ratings
Collaboration
7.20 Ratings
9.00 Ratings
Testing and debugging
7.50 Ratings
9.00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Great: Need to query simpler APIs, or utilize well known services such as GSheets etc.? Matillion has got some of the best and easiest to use connectors out there. Not so great: Do you need have a competent CI/CD flow that you will be able to update / compare from Matillion as well as other sources at the same time? Good luck, you will need to be extra careful, as you might have to have a deeper dive into your servers Terminal each time you have a git conflict.
The same way you design data integration job can be used to design services. It is easy to enhance by custom components and can adapt to all requirements. Talend Data Integration connects to [a] multitude of data sources and streaming service. Very easy interface to design complex applications without spending much time on coding. Easy to learn and master. Talend constantly strives to better itself by adding more features and functionalities.
We used Talend to ETLing the data from myriad sources such Oracle Database, Clarify, Salesforce, Sugar CRM, SQL DB, MQ, Stibo Step, FTP, Netezza, and Files.
We leverage Talend transformation capabilities for stitching the data , unions and join
We successfully created the final unified set that can be used by business
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.
Matillion is easy to use and flexible to debug. Performance are good and support is giving us a good service level. There are still some technical points to be developed more (such as SAP extraction). but easy flows are really fast to be developed. We are also using a tool for migration from other tools, and it is useful as Matillion is producing XML code.
Easy tasks are really easy, and complex tasks are still possible. With prior knowledge of general data warehousing principles and experience with other data transformation tools, it's straightforward to get familiar with and use Matillion. I initially used minimal external support from a partner for some more complex tasks but very soon could work entirely independently with Matillion.
We use Talend Data Integration day in and day out. It is the best and easiest tool to jump on to and use. We can build a basic integration super-fast. We could build basic integrations as fast as within the hour. It is also easy to build transformations and use Java to perform some operations.
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.
Good support, specially when it relates to PROD environment. The support team has access to the product development team. Things are internally escalated to development team if there is a bug encountered. This helps the customer to get quick fix or patch designed for problem exceptions. I have also seen support showing their willingness to help develop custom connector for a newly available cloud based big data solution
We selected Matillion primarily because of it's ability to connect to numerous data sources and easily create transformation jobs. While Fivetran does a better job managing and examining deltas, it is not easy to use and is very non user friendly. SSIS was not a good fit for our team and required a significant amount of attention and server management that we did not want to invest in.
Talend has many built-in components that reduce the development work. We were able to complete the project sooner than expected. Easy to on-board resources as it is straightforward to use. We can manage all the pipelines in the cloud with simple alerting. No major downtimes. Connectors to all new applications in the market.
We're using Matillion on EC2 instances, and we have about 20 projects for our clients in the same instance. Sometimes, we're struggling to manage schedules for all projects because thread management is not visible, and we can't see the process at the instance level.
Time savings -- we could custom code nearly everything Matillion does, but it would take days/weeks instead of minutes/hours.
There's a bit of a learning curve to truly unlock Matillion's potential, and that can be frustrating for some new users, but once you get over that curve, the possibilities are endless.
It allows us to centralize the hundreds of way to bring data in, so that even if you have to troubleshoot what someone else wrote, it's easy to jump in and understand what is happening.
It’s only been a positive RoI with Talend given we’ve interfaced large datasets between critical on-Prem and cloud-native apps to efficiently run our business operations.