Azure Data Observability Tools Compared for Databricks and Purview Teams

Short answer: Azure has no single data observability product. Microsoft Purview scores data quality against rules you write, Azure Monitor watches infrastructure, and neither learns what normal looks like for each table. For tables in Azure Databricks, Snowflake or BigQuery, a monitoring platform such as DataObservability fills that gap from 59 dollars a month. Synapse and Fabric tables are not connected directly today.

Teams searching for Azure data observability tools usually have the same problem. A pipeline loaded late, a column changed type, or a table lost a third of its rows, and the first person to notice was a finance analyst. This article lays out what Azure gives you, what it costs on a realistic estate, and where a separate monitor earns its place.

Azure data observability options compared

The figures for Purview come from the billing documentation we worked through in our Purview Data Quality pricing breakdown, which shows the monthly bill at 50, 100 and 250 tables.

What Purview Data Quality covers and where it stops

Purview Data Quality is a rules engine with a scoring layer. Microsoft documents profiling and quality scans for Azure Data Lake Storage Gen2, Azure Databricks Unity Catalog, Azure Synapse, Azure SQL Database, Fabric, Snowflake and BigQuery. You attach a table to a data product, profile it, write or accept rules for completeness, uniqueness, freshness and similar checks, and read the score that rolls up by asset and domain.

That is a good fit when your checks are precise business rules a steward can state, and when governance already runs in Purview. It is a weaker fit for the silent failure, the one nobody wrote a rule for. Each simple rule run consumes about 0.02 DGPU, which is roughly 0.30 dollars on Basic, so five rules on one table checked daily cost about 45 dollars a month. At 250 tables that is a five figure monthly line if charges follow rules, before anyone counts the steward time to write them.

What Azure Monitor does and does not tell you

Azure Monitor tells you whether a pipeline ran, how long it took and whether it errored. That matters, and it is not the same as knowing the data is right. A Data Factory or Databricks job can finish green and deliver half the usual rows because an upstream export was truncated. The run succeeded, the table is wrong, and no infrastructure alert fires.

Data observability checks the output instead of the job. It asks whether the table was updated when it normally is, whether the row count sits inside its usual range, whether the schema is the same as yesterday and whether the value distribution of key columns has moved. Those four checks catch most of the breakages that reach a dashboard.

A worked example with real numbers

Take a team with 120 tables in Azure Databricks feeding revenue reporting, and a marketing mart of 30 tables that lands ad performance exports from tools such as generatedugc.com next to spend data. That is 150 tables.

• Purview, five simple rules per table, daily on Basic. About 45 dollars per table per month in DGPUs, so roughly 6,750 dollars a month if every scan bills per rule, plus governed asset charges of about 0.50 dollars per table. Microsoft does not publish a per scan quote, so run a one week pilot to read the real meter.
• Enterprise platform. A listing around 45,000 to 50,000 dollars a year, which is 3,750 to 4,170 a month.
• DataObservability Team. 250 tables for 179 dollars a month billed yearly, so 150 tables fit with room to grow. Over twelve months that is 2,148 dollars.

The monitor does not replace Purview rules for exact business facts. It covers the unwritten ones. Many teams run both, with Purview holding the rules that governance requires and a monitor watching everything else.

Which Azure tables DataObservability connects to

DataObservability connects read only to Databricks, including Azure Databricks, plus Snowflake, BigQuery and Redshift. It reads dbt manifest files on Team and above. Azure Synapse, Fabric and Azure SQL are not connected directly, so if those hold your critical tables, Purview or a platform with a native connector is the right route today. If your gold layer sits in Databricks, our Databricks data quality monitoring page shows the setup and what the monitors cover.

How to choose in three questions

1. Where do the tables analysts trust live? If the answer is Azure Databricks, Snowflake or BigQuery, a monitor connects directly. If it is Synapse or Fabric, start with Purview.
2. Are your checks rules or surprises? Rules point to Purview. Surprises, the failures nobody predicted, point to learned monitors.
3. Who carries the contract? A five figure annual commitment needs procurement. A monthly plan can start on a team card, and you can compare it against your current bill on the pricing page.

For a wider comparison of what each platform costs once you read the vendor sources, see our data observability pricing comparison and the enterprise data observability cost analysis. Microsoft documents the data quality service in its Purview data quality overview.

Azure data observability FAQ

Does Azure have a data observability tool?

Not as one product. Purview Data Quality scores tables against rules, and Azure Monitor tracks infrastructure and pipeline runs. Neither learns a baseline per table, so most teams add a monitoring platform for freshness, volume, schema and distribution checks.

How much does Purview Data Quality cost?

At East US list rates, 15 dollars per DGPU on Basic. A simple rule run uses about 0.02 DGPU, roughly 0.30 dollars, and each table in a scan also bills as a governed asset at 0.0165 dollars a day. Pilot a week to read your real meter.

Can I monitor Azure Databricks tables for anomalies?

Yes. DataObservability connects read only to Azure Databricks and builds freshness, volume, schema and distribution baselines on each table. Plans start at 59 dollars a month for 50 tables, with a 14 day trial and no card.

Does DataObservability support Synapse or Fabric?

Not directly today. It connects to Databricks, Snowflake, BigQuery and Redshift. For Synapse or Fabric tables, Purview Data Quality is the supported route, and you can monitor any downstream Databricks or Snowflake copies with a monitor.

Is a data observability platform worth it if I already use Purview?

Often yes, because they answer different questions. Purview checks the rules you wrote. A monitor catches what no one wrote a rule for, such as a late load or a retyped column, and groups the alerts into incidents with lineage.

Ready to see what your tables are doing? Start the 14 day trial and connect a read only role to your warehouse.