5 Key Differences Between Matillion and Xplenty:

  • Contrary to its name, Matillion ETL is actually an ELT product. Xplenty is an ETL/ELT solution.
  • Matillion process transformations after loading. Xplenty processes transformations before or after loading. 
  • Matillion charges by the number of users and saved projects. Xplenty charges a flat rate based on the number of connectors.
  • Matillion uses your data warehouse for processing power. Xplenty has its own data engine. 
  • Matillion takes time to learn and lacks clear documentation. Xplenty empowers any ETL beginner to build data pipelines in minutes.

Matillion ETL and Xplenty are cloud-native ETL/ELT solutions that integrate data between applications, SaaS platforms, DBMSs, and data warehouses. Both platforms feature low-code/no-code user interfaces, a wide range of pre-built connectors, and they’re compatible with the most popular cloud data warehouse systems. 

On the surface, Matillion ETL and Xplenty look similar, but there are key differences that could affect your decision to choose one platform over the other. In this detailed comparison, we’ll explore the most salient features and characteristics that set Matillion and Xplenty apart so you can determine which is best suited for your needs.

Please use these links to navigate the guide:

  1. Overview of Matillion and Xplenty
  2. ELT vs. ETL and ETL
  3. Connectors and Transformations
  4. Customer Support
  5. Disadvantages of Matillion and Xplenty
  6. Final Thoughts on Matillion vs. Xplenty (TL;DR)

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Overview of Matillion and Xplenty

Matillion Overview

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Matillion launched as a cloud-native analytics and business intelligence platform in 2011. Later, it released an ETL (extract, transform, load) solution in 2014. These days, Matillion ETL offers both data analytics and ELT as a service products. 

Technically, Matillion is not an ETL platform because it uses the processing power of your destination data warehouse to perform transformations after the loading phase. In this respect, Matillion is ELT (extract, load, transform), not ETL. 

Depending on your service-level commitment, Matillion’s features may include:

  • ELT capabilities (not ETL): Matillion is an ELT platform that relies on your data warehouse to perform transformation computations after loading. 
  • Cloud-native platform: Matillion is a cloud-native platform that you can access from any internet browser.
  • Cloud data warehouse compatibility: The solution works with popular data warehouse systems like Redshift, BigQuery, Snowflake, and Azure Synapse Analytics.
  • Out-of-the-box transformation: Matillion offers a range of no-code/low-code data transformations that allow you to combine different transformations for more sophisticated transformation requirements. 
  • Prebuilt connectors: Matillion’s 100+ pre-built connectors let you quickly connect with a wide variety of sources/destinations. 
  • REST API connector: The REST API connector enables custom integrations with any source/destination that has a REST API.
  • Workflow automation: Matillion’s automation tools let you create event-, time-, and logic-based task scheduling and workflows. 
  • Real-time monitoring and alerts: Matillion lets you monitor ongoing integration tasks in real-time. You can also create notifications and alerts that Matillion pushes to your email, Slack, and other platforms. 
  • Hand-coded scripting: For advanced users, Matillion allows you to code custom scripts in Python, Bash, and SQL. 
  • Matillion API: The Matillion API lets you interact with the platform, monitor jobs, edit configurations, and perform other actions. 
  • Automatic scaling: Matillion offers redundancy and concurrency by running in a clustered environment. 
  • Permissions and access control: Matillion lets you control access and permissions for individual users and groups of users.

Here’s a screenshot of Matillion’s user interface:

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This user says that Matillion has a difficult time optimizing complex workflows:

“An easy to use tool that has allowed me to build a fully automated data warehouse to report to the business. It was easy to learn and implement, and as difficult as SQL to master. I think the real complexity comes from optimizing complex workflows. The more T you need in the ETL/ELT process, the more Matillion falls down.” - Joe E.

Xplenty Overview

Xplenty launched its cloud-native ETL as a service platform in 2011. The solution offers enterprise-grade ETL services that are easy-to-use and affordable. In fact, Xplenty’s graphical drag-and-drop interface is so quick to learn that anyone -- from a front-desk receptionist to an analyst on your BI team -- can use Xplenty to build sophisticated ETL pipelines and data transformation workflows in minutes. 

Xplenty logo.png

Here’s how one user summarizes Xplenty:

“There are mostly two types of ETL as a service on the market: one is super easy to use and can migrate your data across services and databases but lacks transformation capabilities, while the other needs full-time data engineers to operate but tailored solutions are available programmatically. Xplenty sits in the golden middle letting analysts and engineers deploying custom transformation jobs in minutes even based on multiple data sources.” -Tamas S.

Xplenty’s most popular features and characteristics include:

  • ETL and ELT capabilities: Xplenty’s primary use-case is ETL as a service. The platform features a powerful data engine that performs in-pipeline transformations. It can also manage ELT transformations within the destination data warehouse (like Matillion). 
  • Cloud-native: Xplenty was born in the cloud and lives in the cloud, so you can access it from any internet-connected web browser. The solution does not require additional hardware or hosting. Just log into the platform and Xplenty is ready to use.
  • Easy-to-use interface: Xplenty’s beautiful drag-and-drop interface features an intuitive, no-code/low-code dashboard that anyone can navigate to build nuanced data pipelines, transformations, and automated workflows. 
  • 140 pre-built connectors: The platform boasts approximately 140 native connectors for the most popular sources/destinations -- including databases, data warehouses, SaaS services, apps, and more. 
  • Cloud data warehouse compatibility: Like Matillion, Xplenty works with the most popular data warehouse systems such as Redshift, BigQuery, Snowflake, and Azure.
  • REST API connector: The Xplenty REST API connector makes it easy to quickly integrate with any source/destination that exposes a REST API.  
  • 100+ ready-made data transformations: Use the platform’s prebuilt transformation features out-of-the-box without writing a single line of code.
  • SQL scripting editor and native scripting language: Advanced users can code their own transformations with Xplenty’s SQL editor or the platform’s native scripting language. 
  • Cutting-edge security, encryption, and data compliance: Xplenty complies with SOC 2, GDPR, CCPA, HIPAA, and TLS encryption in transit and at rest.
  • Real-time monitoring and alerting features: The Xplenty dashboard displays real-time progress updates for ongoing tasks (see image below) and automatically sends email alerts when issues arise.
  • Virtually unlimited scaling: Through dynamically-created clusters, Xplenty offers virtually unlimited scaling in response to fluctuating data volume, traffic, and processing requirements. 
  • Unlimited user support: All Xplenty user-level commitments receive unlimited phone, email, and video conference support. Xplenty’s awesome and responsive support team is always available to help you achieve your data integration goals. 
  • Salesforce to Salesforce integrations: Xplenty offers two-way, Salesforce-to-Salesforce integrations so you can pull Salesforce data into Xplenty, transform or enrich the data, and push it back into Salesforce. You can also move data from one Salesforce org to another. These features are usually only available in the most expensive and difficult to use ETL platforms (like MuleSoft, Talend, and Jitterbit). Xplenty empowers ETL beginners to develop secure Salesforce-to-Salesforce workflows quickly, easily, and affordably.  
  • Access control: Xplenty uses firewalls that deny access to external and internal networks by default. Only specifically allowed ports and protocols receive access permissions. Security groups limit access to ports and protocols needed for specific system functions.

Here’s a screenshot of Xpenty’s point-and-click user interface:

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Here’s a screenshot of Xplenty’s real-time job progress monitoring:

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ELT vs. ETL and ELT

Matillion is ELT (Not ETL)

Even though Matillion calls its flagship product “Matillion ETL,” it actually follows the ELT model by using the computational power of your cloud data warehouse to carry out transformations after the load phase like this:

  1. Extract data from the source
  2. Load data immediately into a cloud data warehouse
  3. Transform the data within the data warehouse

The ELT order of data integration is useful when you need to:

  • Ingest any kind of data immediately: ELT gives you the flexibility to extract, load, and save any kind of information as quickly as possible. There’s no need to transform the data into a specific structure before saving it in the data warehouse. This gives you the freedom to capture data now and develop structures for the data later. 
  • Low-maintenance: ELT platforms generally operate in the cloud via automated workflows. Since users don’t have to trigger manual updates, they are low-maintenance systems.  
  • Faster data loading: ELT offers faster loading because the data goes directly into the data warehouse without waiting for the transformation step. 
  • Ideal for data lakes: ELT is well suited for ingesting data into a data lake. Unlike a relational data warehouse, a data lake is optimized for ingesting and storing unstructured data (like photographs or unstructured text information). For analytics purposes, you may eventually need to transform this data into a structured format.

Here are the potential challenges of post-load ELT: 

  • Data compliance challenges: Extracting untransformed (unredacted) information into a destination data warehouse is risky, and in some cases, it could be a violation of certain data compliance standards. For example, if your organization follows HIPAA, SOC2, GDPR, or CCPA guidelines, pre-load transformations may be necessary to remove, mask, or encrypt specific data fields that contain sensitive information. These transformation operations may need to occur before the data enters the destination warehouse. 
  • Expensive processing fees: By shifting the data transformation burden to your data warehouse, Matillion can lower the price of its ELT service. However, using Matillion can get very expensive from a processing fee perspective. Computation expenses for your cloud data warehouse will grow as your data requirements expand. Due to fluctuating monthly demands, it will be difficult to predict your data integration expenditures from month to month.

As a result of Matillion’s push-down ELT strategy, the platform might not be appropriate for companies that need to follow strict data compliance standards while managing large-volume, complex transformation workflows. On the other hand, Matillion could appeal to organizations that need to quickly ingest and store large amounts of unstructured data.

*This white paper offers more information about the differences between ETL and ELT.

Xplenty Is Both ETL and ELT

Unlike Matillion, Xplenty includes a powerful data engine that processes ETL jobs in the following order:

  1. Extract data from the source and load it into Xplenty
  2. Transform the data in-pipeline with the Xplenty data engine
  3. Load the information into a cloud data warehouse

If your use-case requires it, Xplenty can also perform post-load ELT transformations the way Matillion does (by using the compute power of your cloud data warehouse). However, Xplenty’s flat-rate pricing structure means that you can use the Xplenty data engine to perform these operations without an additional charge. Most Xplenty customers choose to save money on data warehouse processing fees by using the Xplenty data engine to perform ETL transformations before loading.

Here are two advantages of Xplenty’s unlimited in-pipeline transformation capabilities: 

  • Improve data security and compliance: In-pipeline transformations can remove sensitive information before loading it into the destination. This makes it easier to secure your data and satisfy industry compliance standards.
  • Save money on processing fees: With Xplenty, will never pay extra when processing requirements or data volume increase from month to month. Xplenty’s per-connector pricing offers a predictable billing structure that doesn’t change unless you add or remove a data connection. 

As an ETL solution that performs in-pipeline transformations, Xplenty does not burden your data warehouse with additional processing demands. This prevents you from incurring auxiliary costs when data integration requirements expand.

Connectors and Transformations

Matillion Connectors and Transformations

Matillion offers approximately 100 pre-built connectors for frequently-used databases, data warehouses, SaaS services, and applications. It also includes a REST API connector that facilitates custom integrations that aren’t on the list of connectors. 

Here’s a small sample of Matillion’s connectors:

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Matillion offers no-code/low-code data transformations. It also allows developers to hand-code transformations in Python, SQL, and bash. 

Xplenty Connectors and Transformations

Xplenty includes approximately 140 pre-built connectors for the most popular database systems, data warehouses, SaaS services, and apps. It also has a REST API connector for creating fast, custom integrations when a native connector isn’t available. 

Here are some of Xplenty’s native connectors:

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Among these pre-built integrations is Xplenty’s popular Salesforce-to-Salesforce data connection. This connector allows you to extract data from your Salesforce org, transform/enrich it in the Xplenty data engine, then load the changed data back into Salesforce. You can also use Xplenty’s Salesforce integration to migrate data from one Salesforce org to another, which allows you to synchronize Salesforce data across various organizations, partners, and departments. 

Finally, Xplenty includes more than 100 no-code transformations that empower anyone -- from absolute beginners to experienced data engineers -- create transformations and automated workflows for FILTERing, JOINing, SELECTing, LIMITing, and CLONing your data in-pipeline. Experienced developers can still enjoy hand-coding their transformations in SQL or Xplenty’s native scripting language.

Customer Support

Matillion User Support

All Matillion ETL users have access to support by email and phone, but it’s not clear based on the Matillion website whether the platform limits you to a specific number of support tickets. 

Here’s what users are saying about Matillion customer support: 

“The support team has been very responsive in resolving some Azure-related issues, tuning our instance, and helping to understand the nuances of how it works.” -Brian R.

“The support team was always very helpful most of the time, only having faced a few issues because of time-zone differences when solutions are required immediately and I couldn't reach anyone. In most of the cases, the support is exceptional.” -Sudarshan Koshari

Xplenty User Support

Regardless of the service level commitment, every Xplenty account receives unlimited user support from a dedicated integration specialist. In fact, Xplenty’s awesome user support is a key component of the platform’s success at empowering complete ETL novices to build sophisticated, enterprise-grade data pipelines. In fact, your Xplenty integration specialist will feel like an expert member of your team, who is with you every step of the way and is available by phone, video conference, and email to help you build the integrations and workflows you need. 

Here’s what reviewers say about Xplenty support:

“As a bonus to the product features, Xplenty has excellent customer service. The team goes above and beyond to work with us to develop our data flows and answer any questions we have about the product in their real-time chat system. If bugs or feature requests are discussed, the support team works with us to find adequate workarounds and keeps us in-the-loop while the fix/feature is implemented.” -Lally B.

“What we love best about Xplenty is the near real-time support we get from the team. Xplenty's point of difference is the customer support we receive. The product itself is good. Easy to use at a high level. The people at Xplenty are the difference – which is unusual for Cloud proposition. A nice change from dealing with a faceless machine.” -Jamie B. 

“Do not hesitate to contact XPlenty's live support. They will get you up and running in no time and will help you sort out common strategies in designing your pipeline.” -User in E-Learning

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Disadvantages of Matillion and Xplenty

Disadvantages of Matillion

Users should be aware of the following potential disadvantages of the Matillion platform:

1) Difficult to use: Though Matillion ETL touts itself as an easy-to-use platform, this platform is intended for operators with some level of ETL and SQL experience. Documentation for the platform isn’t very user-friendly, and numerous customer support calls may be required before you start feeling comfortable with Matillion -- even if you have a lot of ETL experience.

Here’s what users say about this:

“It has been an ongoing learning curve for a year. The basics [of Matillion] are simple to pick up but after that, you have to turn to support for answers as there is nothing on the web. Support can take days to get an answer after emails are sent back & forth to gather the information required to answer your questions.” -Mark Austin

“I found it clunky to use at first, non-intuitive. I did not find the online documentation to be very helpful, I never did find a video tutorial that spoke to my needs, and some of the terminology ("orchestration" and "transformation") I still find a bit opaque, and the division of different types of functions into the blue and green widgets doesn't always make sense to me. But I've managed to put together a fairly complex set of components that does most of what I want it to do…” -John S.

2) Lacking two-way integrations: While the most advanced, enterprise-grade ETL platforms offer two-way integrations (such as a Salesforce-to-Salesforce integration that lets you extract data from Salesforce, transform it in-pipeline, and push it back into Salesforce), Matillion is simpler, and two-way integrations like this aren’t possible. Moreover, once Matillion puts data into your data warehouse, there’s almost no way to extract it and integrate it with another destination.

Here’s what one user says about this:

“There is almost no ability to get data back from your warehouse into the other systems to synchronize the data. It's great to have it all in the warehouse, but it seems pretty critical to have that data flowing back to other systems that are part of your environment… We quickly realized that we would need yet another tool to get the data back out to the source systems to synchronize/integrate it. We could sort of do it with Matillion, but it required a lot of custom programming and was not very intuitive. We ended up using a different iPaaS tool that could handle traffic/integration in both directions.” -Michael S.

3) Inefficient for high data volumes and complex transformations: Experienced ETL developers describe Matillion as a “beginner ETL” product suitable for new ETL users and smaller teams. As you scale into large-volume ET processes, and complex transformations involving many data sources, you could find Matillion to be increasingly difficult to use, slow, inefficient, and overpriced for large volume requirements. 

Here’s what users say about this:

“Excellent entry-level ETL/ELT resource. Matillion is great for a team's first foray into ETL. It holds your hand exactly as much as is needed and scales brilliantly within the scope of a small team. It becomes less ideal as you add more data sources and processing… Resource use can balloon when performing even moderately-complex transformations, and race conditions still have a tendency of appearing when more than a few processes run concurrently… It interacts well with Python, but any other scripting is harder to integrate.” -Adam Labay

"It is highly insufficient when executing commands parallel and does not utilize the resources to its full potential. The environment limitation is also very problematic when trying to scale." -Capterra Reviewer

Disadvantages of Xplenty

Users should be aware of the following potential disadvantages of the Xplenty platform:

1) Slightly higher base fees: Xplenty’s fee structure starts a little bit higher than Matillion. However, the value of Xplenty shines when managing larger-volume integrations and complex transformations. Xplenty’s flat-rate pricing structure offers enormous cost savings on multiple fronts: unlimited data volume and processing, no additional costs for expert labor, and no additional costs for servers/hosting.

Here’s an example of Xplenty’s cost-saving potential at work:

“Xplenty’s data integration saves Grofers at least 480 hours of data engineering time every month: the equivalent of hiring four data engineers. Analysts can quickly leverage data insight from Xplenty without relying on data engineers or worrying about the underlying infrastructure.” -Xplenty Customer Case Study

2) Different opinions on graphical UIs: The Xplenty user interface is a boon to ETL beginners and busy data engineers who need to build sophisticated data integrations fast. That withstanding, you may need to convince some veteran engineers to embrace Xplenty -- especially if they prefer hand-coded integrations. One way to do this is to show experienced engineers how much time Xplenty saves, and how it empowers departments to manage data integrations on their own. Experienced engineers will also appreciate Xplenty’s SQL editor and native scripting language. 

Here’s how one data engineer describes using Xplenty:

“After evaluating 10 or so ETL providers I went with XPlenty because their service has a relatively straightforward GUI, but also allows for a fairly sophisticated level of configuration. Most of the time the GUI is sufficient, but I'm also able to script bits and pieces and add custom SQL to handle the weird edge cases or make some of the large transfers more efficient (e.g. using a custom date field). I'm also able to do data transformations as part of the pipeline.” - Mike B.

Here are some additional user reviews about Xplenty:

“Xplenty is on PAR with enterprise-level tools.” -Guru Kiran S.

“The customer support is one of the best I have experienced. They were very prompt every time I would have an issue with using Xplenty. Moreover, the development team is also quite fast, as they were able to implement pagination for an API I was using in less than 2 days.” -Alexandru B.

Final Thoughts on Matillion vs. Xplenty (TL;DR)

Now that we’ve looked at the details of Matillion ETL vs. Xplenty, you should have a better sense of the platforms and their differences. Here are the most important aspects of Matillion and Xplenty that we covered in this guide:

Matillion ETL, despite its name, is a cloud-native ELT platform with the following characteristics: 

  • Like Xplenty, Matillion includes a graphical UI and a wide variety of pre-built connectors and ready-made data transformations. 
  • As an ELT solution, Matillion offers fast extract/load and the flexibility to quickly ingest unstructured data.
  • According to online reviewers, Matillion is easy to learn compared to other ELT platforms. One user said that Matillion was about as easy to learn as coding in SQL. 
  • Post-load ELT transformations could be troublesome from a data compliance perspective if you are moving unredacted information into a new storage solution. 
  • Matillion uses the processing power of your data warehouse to manage transformations after loading. This means that will be responsible for processing fee costs of the post-load transformations your data warehouse performs. 

Xplenty is a cloud-native ETL/ELT solution with the following characteristics:  

  • Xplenty is unique because it offers a “best-of-both-worlds” solution that combines enterprise-class ETL/ELT with ease of use and affordability. 
  • Xplenty’s easy-to-use interface and responsive support team liberate you from the need to rely on IT staff and data engineers to set up data integrations and transformation workflows.
  • Xplenty allows any non-tech-savvy employee to quickly build sophisticated ETL pipelines.
  • Xplenty’s amazing support team is a key bard of empowering ETL beginners to use the platform.  
  • Xplenty’s flat-rate billing structure is affordable and predictable when planning monthly budgets (fees don’t change unless you add/remove connectors). 
  • Xplenty’s unlimited, in-pipeline transformations save you money on data warehouse processing fees. 
  • Xplenty adheres to the most popular data compliance and regulatory guidelines to keep your data safe.

At the end of the day, Xplenty has empowered countless organizations to solve their data integration challenges while eliminating auxiliary costs, saving money, and freeing IT staff to work on more important functions. 

Get started on Xplenty today.