25 reviewers had the following to say about Matillion's features:
We shortlisted three different ETL tools based on the capabilities to perform full load, incremental load with change data capture (CDC), process chains, job scheduling and monitoring, job success/failure notification to name a few most important criteria.
Pros
Quick development capabilities to perform full load, incremental load with change data capture (CDC), process chains, job scheduling and monitoring, job success/failure notification, customer support to name a few
Cons
Wish to see Matillion having Github control
Rating breakdown
Time used: 1-2 years
Frequency of use: Daily
Likelihood to recommend
Their support team are also very responsive, and Matillion are always keen to help you get the most out of their software, so there's a lot of support if you want it. 2+ years later, and we're using Matillion to run all our ELT jobs across various data warehouse projects, and very happy with it.
Pros
. - Lots of third party integrations.
Cons
- User concurrency/licencing model (simple, but can't be customised to fit your need). - Exception handling could be improved. - A single Task View would be helpful for multi-environment/project support.
Rating breakdown
Time used: 2+ years
Frequency of use: Daily
Likelihood to recommend
We're pulling multiple datasets together and integrating them in star schemas with Matillion, as well as doing sophisticated data analysis.
Pros
The GUI and design makes it easy to not only functionalize your ELTs, but also show a graphical DAG to stakeholders.
Cons
I wish it had an out-of-the-box API gateway to receive webhook requests from third-party data sources.
Rating breakdown
Time used: 6-12 months
Frequency of use: Daily
Likelihood to recommend
Matillion's cloud model is leading the trend in this industry. It's cost effective and manageable.
Pros
I've worked with a larger number of clients that have uses Matillion as well as other tools and Matillion is definitely the most reliable. The UI is easy to follow and understand and the learning curve is small.
Cons
It does require some training or knowledge of workflow development though it's the most reliable.
Rating breakdown
Time used: 1-2 years
Frequency of use: Occasionally
Likelihood to recommend
Speed of ETL development and templated approaches.
Pros
I could build a complete ETL process with absolutely no training at all in just a few hours. All of the components I expected to see where there, and heaps more. When I needed help - there it was!
Cons
Versioning and branching is difficult when developing, there is a total reliance on a unique component name.
Rating breakdown
Time used: Less than 6 months
Frequency of use: Daily
Likelihood to recommend
We use the tool for creating ETL data piplines.
Pros
Easy learning Curve Simple to work with Cloud based tool Great support Very easy to support shared code due to the GUI element.
Cons
Lack of DevOps style integration Lack of release management support.
Rating breakdown
Time used: 6-12 months
Frequency of use: Daily
Likelihood to recommend
Its' ability to blend a ton of out-of-the-box functionality with the ability to script custom components in Python to author our own integrations is invaluable.
Pros
-Easy to use UI to build complex transformations.
Cons
-No automated scheduling based on dependent table updates. (This is possible to set up, but not out of the box.) -Support SLAs have gotten worse over time.
Rating breakdown
Time used: 2+ years
Frequency of use: Daily
Likelihood to recommend
I like working on matillion , but this tool can be made more flexible by providing some of the additional features.
Pros
1) Most of the components are user friendly. 2) Development of ETL orchestrations and transformation consumes less time. 3) Advanced features are available in some of the components makes the complex scenarios achievable.
Cons
1) OAuth document does not provide the details of proper permissions and access levels on account_id or client_id which are required for a connector. 2) Differentiation of naming convention of metrics between the console and matillion data model , mapping document of these naming conventions is not available. 3) Connector for Outbrain is not available. 4) Indirect file loading concept is not available , for example if we have five files with same structure , reg ex can not be used to load all files in a single component(s3 load,s3 put or excel) and need to use the file iterator. 5) Loss of properties when the component configuration is changed from Basic to Advanced features , ideally the component should include all the properties of basic and then additional setting should be provided.
Rating breakdown
Time used: 6-12 months
Frequency of use: Daily
Likelihood to recommend
So far i have had integrated bunch of sources using Matillion to data warehouse.
Pros
It has most of the connectors for all data sources which makes my job to complete end to end development.
Cons
One thing I did not like about Matillion is, there is no need of Transformation job. Everything should be done at one place(Should be in Orchestration job). Also, the list of components are different in Orchestration and transformation jobs.
Rating breakdown
Time used: 6-12 months
Frequency of use: Daily
Likelihood to recommend
I am happy with this tool and it has good UI.
Pros
- It has very good UI to design the workflow. - It is easy to design the workflow. - It has very good support with persistence storage.
Cons
- It should also support Azure data warehouse.
Rating breakdown
Time used: 2+ years
Frequency of use: Daily
Likelihood to recommend
Great. Good customer service, quality product.
Pros
Makes for very fast development with lots of built in connectors.
Cons
We use this for a lot of production applications. After 1 year of trying to fix OOM errors and doubling our instance size, we still get them monthly.
Rating breakdown
Time used: 2+ years
Frequency of use: Daily
Likelihood to recommend
If you're looking for a tool for your analytics data warehouse which is fast, convenient and easy to learn, then this is the tool for you
Pros
Its very easy to learn. The UI is great and easy to navigate.
Cons
Its a one way ETL, I'm using the BigQuery product and all the destination are in BigQuery, it would also be nice if we can load data to the sources.
Rating breakdown
Time used: 1-2 years
Frequency of use: Daily
Likelihood to recommend
We have been using Matillion for constructing data tables for analytical purposes.
Pros
Matillion provides a graphical representation of any SQL query.
Cons
Interactions with external custom APIs can be a bit of a pain, but we've always managed to get there one way or another.
Rating breakdown
Time used: 6-12 months
Frequency of use: Weekly
Likelihood to recommend
I think the real complexity comes from optimising complex workflows, the more T you need in the ETL/ELT process, the more Matillion falls down.
Pros
It is easy to use and quick to get started, there are many inbuilt APIs and transformations that integrate it across a broad suite of systems, and enable you to transform data for the business without having to spend too much time thinking about scripts or bespoke batch files.
Cons
The filter transformer is pretty minimal considering the power of the SQL it is utilising, it cannot use compound logic or reference other columns/objects in the query.
Rating breakdown
Time used: Less than 6 months
Frequency of use: Daily
Likelihood to recommend
Storing data in Google Big query allows seamless access to it from other Cloud Products I.E.
Pros
My background is development and I love the simplicity of the Matillion, you can very easy transform your thought process into blocks in Matillion, and debug any issues at a very granular level.
Cons
Matillion crashes from time to time, meaning you need to log back on to the system, but its benefits definitely outweigh this small issue.
Rating breakdown
Time used: 6-12 months
Frequency of use: Daily
Likelihood to recommend
We could sort of do it with Matillion, but it required a lot of custom programming and was not very intuitive.
Pros
It is extremely fast and easy to pull data from various sources and pipe it into Snowflake.
Cons
With it shut down, development can't happen.
Rating breakdown
Time used: 6-12 months
Frequency of use: Occasionally
Likelihood to recommend
Overall it is user-friendly, easy to develop & deploy, secure ELT for big data use cases.
Pros
1) Easy to use 2) Several ingestion integrations 3) Custom RDBMS ingestion support 4) Robust transformation and Orchestration components
Cons
No availability of change data capture feature for many databases
Rating breakdown
Time used: 6-12 months
Frequency of use: Daily
Likelihood to recommend
In the scope of a sole user, it's a very powerful tool.
We are loading customer data to provide reporting and analytics.
Pros
We have been able to get it set up and are starting to load data for our customers.
Cons
Too soon to tell, as we just started using the product. We are not yet formally in production as yet.
Rating breakdown
Time used: Less than 6 months
Frequency of use: Daily
Likelihood to recommend
Yet a lot possible with python scripting feature.
ELT, daily basis extract of data and ad-hoc tasks
I was developed around 20 to 50 mapping using Matillion and I don't see any difficulties right know.
Pros
User interface is very easy and any one can mange development things without too much of knowledge.
Cons
I don't see straight forward job Audit framework. Please try to build nice job monitoring and audit framework.
Rating breakdown
Time used: 1-2 years
Frequency of use: Monthly
Likelihood to recommend
It's been a significant reduction in development time since we migrated to Matillion.
Pros
Simple, intuitive interface. I replaced a complicated series of scripts, "ETL" products, and Python code with a simple-to-understand Matillion instance.
Cons
We use it on Snowflake for Azure, so there are several features that have not been migrated from the AWS version, yet. An option for a larger server by default in the Azure Marketplace.
Rating breakdown
Time used: 6-12 months
Frequency of use: Daily
Likelihood to recommend
Matillion helped us develop various business use cases: Ambient temperature monitoring, ERP data centralization, data quality management.
Pros
With Matillion, you can harness the power of major cloud data warehouses in no time.
Cons
Error management and replay can be tricky to develop.
Rating breakdown
Time used: 6-12 months
Frequency of use: Weekly
Likelihood to recommend
