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 -monitor your data health and pipeline performance

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.

Learn more

What makes pipeline management a pain

To manage growing responsibilities, data teams are working with more complex infrastructure and pursuing higher speeds of release – making it harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs.

Inconsistency

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

Blind Spots

Engineers don’t have the full context they need to understand the health of their pipelines and data deliveries

Fragmentation

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
4

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

Native to your data stack

Quickly integrate with best of breed data pipelining tools.

Orchestrators

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

Code

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.

Data

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

All integrations

Powered by open source

Databand’s monitoring solution is enabled by our open source library, giving our users transparency and control

1
Connect

Use open source connectors to integrate your orchestrators, job engines, and metadata libraries.

2
Run

Databand connectors will automatically record metadata as your pipelines run, alerting on important changes.

3
Extend

Add additional connectors, operators, or logging methods for deeper monitoring.

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.