Best modern data quality tools

The modern category includes Monte Carlo, Bigeye, Anomalo, Validio, Soda, Elementary, Sifflet, Telmai, DQLabs, Qualytics, and DataKitchen TestGen, among others. They differ most on how tests get created and how they are priced. Most meter by table; TestGen generates tests from profiling and prices flat.

At 10 users and 1,000 tables, most enterprise tiers land between $60,000 and $250,000 a year, against an industry average near $172,500. TestGen Enterprise is $12,000 to $36,000 at the same size, and the open-source edition is free.

Only a handful do it without qualification: DataKitchen TestGen, Anomalo, FirstEigen, Telmai, DQLabs, and Qualytics. Many others list it as partial, meaning suggestions you still review and author. That distinction decides whether coverage across thousands of columns is realistic.

Soda Core, Elementary, Evidently, DQOps Community, and DataKitchen TestGen and Observability. The important difference is what the open edition can actually do: several are entry points into a paid cloud, while TestGen's open source is the same engine the enterprise edition runs.

How tests get created, because that caps coverage more than any feature. Then where they execute, since running inside your warehouse avoids shipping rows to a vendor. Then how the bill changes when your table count doubles, which is the growth you are actually planning for.

Because we built it, and the matrix scores it honestly including where it does not lead, such as column-level lineage. The methodology and sources are published at the bottom of every page so you can check any row rather than take our word for it.