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Monitor your data health and pipeline performance

Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers.

Observability platform for data engineers - databand

Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up.

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More pipelines, more complexity

Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs.


Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery

Blind Spots

Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust


Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems

Our solution for unified pipeline monitoring

Empowering data engineers to be proactive and productive through deep visibility into pipeline metadata.

Dataframe column structure has changed
Task duration has exceeded its threshold
Peak memory consumption detected
Python error on undetected column
Reliable results

Quickly catch when pipelines deviate from normal baselines

Complete visibility

Track all information in one place – data quality, data lineage, system resource information, and job durations

Centralized tracking

Integrate metadata from all data infrastructure levels, from orchestrator to data lake

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Stay on top of your critical run info, task logs, and data quality metrics with a data engineering approach to logging and tracking. When problems arise, trace the root cause with the ability to analyze metadata across pipelines and over time.

Native to your data stack

Quickly integrate with best of breed data pipelining tools.


Capture schedule and run information from your schedulers, CRON systems and orchestrators.


Consolidate logs and error messages from your data ingestion, ETL, and ML code.

Job engines

Understand performance and resource consumption levels from databases and data compute engines.


Track data quality metrics and data lineage across pipeline input and output, files, and data tables.

All integrations

Used by data teams worldwide

From startups to Fortune 500 companies, we’re helping data engineering teams introduce stable, reliable, and predictable data operations.

Start a free trial or demo

Contact us for a free trial or to see a demo of the solution in action.