Unification Anxiety: The reasons people say no to Matia

When it comes to unifying your data stack around Matia, our customers get excited.

“You mean I don’t have to buy four tools, spend time integrating them, and deal with the headaches like security and governance that come along with it?” 

Yes. Exactly.

And although there is excitement, the fear of the unknown is alway met with a little apprehension as well.

There are typically a few points that are brought up that customers want answers to before committing.

Instead of making you get on sales calls (we still welcome it, obviously) and waiting for you to bring these up, we wanted to address them head on. Here are the two main themes we hear:

1. Migrations are too cumbersome
2. If I switch to a platform, I loose some functionality

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Migrating to Matia

Despite a lot of vendors calling tool migrations seamless, they still do require effort. However, with robust engineering and reliable support, we can take A LOT of the pressure off of our customers.

From an ingestion standpoint, we’ve built Matia to be fully backwards compatible with Fivetran. Users can move to Matia without disrupting their current data workflows. Many of our customers that migrated from Fivetran to another point solution prior to working with Matia had to essentially rebuild their pipelines from scratch. With Matia, all you need is a single schema name change. With auto-generated monitors covering freshness, row count, and schema changes, onboarding Matia observability capabilities is also seamless (we mean it!). 

Migrations can also be speedy. It took Honeybook a few hours to migrate a substantial volume data to Matia from a legacy ingestion/ETL provider. Once done, they were able to boost replication speed by 30% compared to a legacy solution.

Point solution to platform: how you gain functionality 

The other major point of contention is moving from a point solution to a platform. Platforms are nice in theory, but based on prior experience with them, many customers believe that if you are going to widen your product purview, you will lose functionality along the way.

We cannot speak for other platforms, but with Matia, the opposite is true. You actually gain functionality through the unified platform approach.

Take data observability, by integrating observability and ingestion into one platform, customers can be alerted of data anomalies at the point of ingestion - before the data even lands at your snowflake or databricks environment. Other observability solutions will monitor if ingestion failed, but not natively  alert you to anomalies within the data. They will however be sure to look into the data at a later (relatively random) time after those anomalies have already potentially made their way into your transformation layer.

When it comes to reverse ETL, we know you can orchestrate your way and have your Airflow get the dbt job to trigger that new reverse ETL pipeline just on time. But we wanted you to know that with Matia we reduced that process down to two clicks. 

Another thing we’ve found is data teams today tend to be over-platformed. While some solutions may have certain functionalities, when you dig into, their teams don’t have a use for them with their current stack.

So there it is. We’re big believers that companies should have the infrastructure to scale when they’re ready without the headache of going through procurement and integrating a new tool, but they don’t have to loose functionality or sleep when they’re doing it. 

Hopefully we saved you a sales call (and may have addressed your concerns as well).