Cloudera​

Why QuerySurge + Cloudera

Full coverage across the Cloudera ecosystem
QuerySurge connects to Hive, Impala, HDFS, HBase, Kafka outputs, Parquet files, ORC files, and more. This gives you end-to-end validation across every data source and processing layer you run on Cloudera.

Purpose-built for large, distributed data sets
Cloudera workloads produce high-volume, high-variety data. QuerySurge executes distributed queries through its Agents, compares results at scale, and captures exceptions down to the row and column.

Accelerates modernization and migration
Whether you are optimizing your on-prem Cloudera environment or moving workloads to cloud platforms like AWS, Azure, or GCP, QuerySurge validates each stage to reduce risk and speed cutovers.

Consistent testing framework across hybrid environments
Most Cloudera deployments connect to downstream warehouses, BI tools, or cloud platforms. QuerySurge provides a single automated testing system across the entire chain, so you can validate data wherever it lands.

How It Works

Connect QuerySurge Agents to Cloudera Services
QuerySurge uses JDBC drivers to connect to Hive, Impala, Spark SQL, HDFS file formats, Cloudera Data Warehouse tables, and Cloudera Data Engineering pipelines via output tables.

Run Automated Queries Against Source and Target
You define source queries against Cloudera data stores and target queries against downstream systems such as cloud warehouses, operational stores, or BI extracts. QuerySurge executes both sets of queries in parallel.

Compare and Detect Issues at Scale
QuerySurge performs a complete dataset comparison, identifying missing or mismatched records, failed transformations, schema changes, precision or type drift, and business rule violations.

Integrate Into CI/CD and DataOps Workflows
QuerySurge plugs into Jenkins, GitLab CI, Azure DevOps, Airflow, and Cloudera Data Engineering job flows

This allows you to run data quality checks automatically after each pipeline run or code commit.

Produce Audit-Ready Reports
Every test run generates detailed, timestamped, exportable reports for compliance, engineering, and business stakeholders.

Key Benefits

Benefit	Why It Matters
End-to-end data confidence	Validate every step of your Cloudera pipeline from ingestion to analytics.
Faster troubleshooting	Pinpoint the exact row and field where data breaks so engineers can fix issues quickly.
Improved data reliability	Catch transformation errors, drift, schema changes, and data loss before they reach BI dashboards or machine learning models.
Reduced manual effort	Replace sampling and spot-checks with automated full-data validation.
Support for hybrid modernization	Validate data as it moves from Cloudera to cloud data warehouses or data lakehouse platforms.