Deliver trustworthy data.
reliability
issues are
overlooked
Improved Mean Time to Discovery
Discover issues before data consumption
Improved Mean Time to Resolution
Instantly trace the cause of incidents
Improve data product SLAs
Enhance trust and consumer satisfaction
Observability
data observability.
data teams
3/5
Top US banks use Databand
10x
Average improvement of mean time to resolution
360
Data quality monitoring for pipelines and at-rest
30+
Supported integrations for data observability
data engineering
Detect data incidents early, resolve them fast, and deliver trustworthy data.
Detect earlier
Pinpoint unknown data incidents, and reduce mean time to detection (MTTD) from days to minutes.
Resolve faster
Improve mean time to resolution (MTTR) with incident alerts and routing from weeks to hours.
Deliver trustworthy data
Ensure confident decision-making for business consumers and keep customers happy.
Let’s face it. There are a lot of data observability solutions out there. Here’s why Databand’s “shift-left” approach is different. Unlike others that only monitor data-at-rest in your warehouse, Databand provides a continuous data observability approach that ties directly into all stages of your data lifecycle, starting with your source data..
IBM Databand
Continuous Observability
End-to-end observability
Focused on data-in-motion + data-at-rest (from data pipelines to lakes to warehouses)
Real-time alerting on pipeline execution
Custom alerts for data SLAs
Cross tool data lineage and impact analysis
Others
Reactive Observability
Singular focal observability
Focused only on data-at-rest (warehouse only)
Retroactive alerting on table inspection
Incomplete metadata collection for SLAs
Siloed lineage within each tool
Collect metadata
Automatically collect metadata from your modern data stack like Airflow, Spark, Databricks, Redshift, dbt, and Snowflake.
Profile behavior
Build historical baselines based on common data pipeline behavior and get visibility into every data flow, from source to destination.
Detect and alert data incidents
Detect high severity data reliability errors that impact your most critical pipelines and alert impacted teams.
Resolve the root cause
Create smart communication workflows to resolve data quality issues & meet SLAs.
DataOps management
Incident Management
Improve data reliability and quality under one roof with a single pane of glass for all your data incidents.
End-to-end Lineage
Visualize how data incidents impact upstream and downstream components of your data stack.
Data Reliability Monitoring
Monitor data pipeline errors such as failed runs, longer than expected durations, missing data operations, and unexpected schema changes.
Data Quality Metrics
Continuously validate data quality with dataset metrics for SLAs, column changes, and null records.
Anomaly Detection
Eliminate the unknown by seeing trends & detecting anomalies from your metadata in real-time.
DataOps Alerting and Routing
Customize incident alerts and route notifications to impacted DataOps teams for faster resolution.
Databand’s combined capabilities provide a one-stop-shop for all your data incidients. Now platform and data engineers can focus on building. not fixing their modern data stack.
