Matillion Reviews and Ratings

Use Cases and Deployment Scope

We use Matillion for data warehousing solution and building scalable and optimized pipelines to transfrom data. Also we use it to schedule the data pipelines to ensure the data refresh will happen on time.

Likelihood to Recommend

It is easy to understand and use. By simply drag and drop components we can build optimized and scalable pipelines for data warhousing solutions.

Use Cases and Deployment Scope

Use Matillion to fetch data from third-party apps to our own app

Likelihood to Recommend

It's is well suited to fetch data from external apps and transform it.

Use Cases and Deployment Scope

We use Matillion to build, manage and control our data pipelines for our various data warehouses in Snowflake data cloud platform.

Likelihood to Recommend

Building data pipelines in a data cloud environment using Snowflake as target database.

Use Cases and Deployment Scope

Matillion is used as the preferred ETL / ELT tool in our organization and has everything that we need for managing and maintaining our data warehouse in Snowflake. The built in connectors and integration with DevOps git makes pipeline creation very easy resulting in high productivity of Data Engineers. There is very detailed documentation available and Matillion support is very responsive. We have moved from a traditional on premise data warehouse to a cloud data warehouse and Matillion has made this transformation easy and sustainable.

Likelihood to Recommend

Matillion is well suited to maintain and manage our layered architecture based on medallion architecture principles. It caters to most of the data sources we have in our organization and also it has version controlling and documentation capabilities built in. It also integrates nicely with cloud platforms, Azure in our case for secure connections with key vaults.

The only drawback it has is when we need real time data update as we cannot keep the VMs on all the time for cost control. But again it is not built for that purpose.

Use Cases and Deployment Scope

As a digital company we do have several different B2B and B2C systems. Mostly their data is about the same but as anywhere else, nothing is unified. We use Matillion in order to load all of the different source systems and transform and unify the data. It fully empowers our DWH based on AWS redshift.

Likelihood to Recommend

An overwhelming system landscape with different types of databases and APIs to deal with. For generating complex SQL statements and having them nicely displayed to a full overview.

Use Cases and Deployment Scope

We use Matillion ETL as an orchestrator, source ingestor and partially as a transformation tool. We utilize its connectors to query multiple sources, organize these pulls into neat interconnected flows and run initial transformations. Additionally, we use the native Git integration to have a proper development pipeline with the CI/CD flow.

Likelihood to Recommend

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.

Use Cases and Deployment Scope

We have a snowflake cloud data platform setup which host data from wide variety of sources and we rely on Matillion ETL to bring data from source into snowflake. Matillion gives us flexibility to connect to wide variety of sources and we built automation using Matillion and bring data into snowflake to further give business insights.

Likelihood to Recommend

Matillion is a good orchestration tool to build automated ETL Pipelines and has wide variety of connectors. They offer connections to different cloud platforms. It has various connectors available which can be used to fetch data from multiple sources into different cloud data warehouse. Its a modern cloud ELT platform. Its not that great for large data loads.

Use Cases and Deployment Scope

I use Matillion to ingest data from API sources for our POS, Inventory management system, audits and Reviews platform. The business problems that I solve are relating to sales, finance, inventory count and audit scores. All the transformation for our raw data also occur inside Matillion before loading data into the data marts

Likelihood to Recommend

It is very well suited for custom API integrations and orchestrating pipelines. More built in connectors could also help. For data transformation, dbt type format which is very suitable for sql users is missing. Overall, i think Matillion is great for quick and easy pipeline orchestration and complex data transformation

Use Cases and Deployment Scope

Matillion ETL is used by us to create the data pipelines to extract the data from the clients source systems and ingest it into snowflake and perform some transformations within the pipeline. Even after inserting the data to the raw layer in snowflake we create some pipelines to read the data from the raw layer and transform it for some reporting purposes and insert it into consumption layer for bi tool to read the data from there.

Likelihood to Recommend

wherever there is a need of extracting the data from multiple sources and loading the data in any data warehousing tool while performing certain transformation during the pipeline run and you don't have much coding expertise and need to save the time and efforts then Matillion is the best suited tool to do that.

Use Cases and Deployment Scope

Matillion ETL is being used by our datamanagement team for the ingestion of data from our organisation into the datawarehouse in Snowflake and for transforming this data through the datawarehouse to the acces layers for our end users

Likelihood to Recommend

It is depending on the usecase. For a combination of ingestion and transformations it can be a good choice