Big Data
Complex Volumes, Critical Challenges
See how QuerySurge can automate the
testing of Big Data systems
Big Data, Big Risk
Ensure Your Analytics Are Built on Trusted Data
Discover why validating your Big Data pipelines is essential, and how to eliminate costly data defects before they reach your BI reports.
What Is Big Data?
Big Data refers to vast volumes of information stored on platforms such as Hadoop data lakes and NoSQL data stores.
Which data storage technologies are considered Big Data?
Technologies designed to handle massive, distributed data storage at scale.
Big Data Stores
- Hadoop (HDFS): Foundational distributed storage for on-prem clusters.
- Apache HBase: NoSQL database built on HDFS for real-time read/write access.
- Apache Cassandra: Distributed NoSQL database optimized for high availability.
- Amazon S3, Azure Data Lake Storage (ADLS), Google Cloud Storage: Cloud object stores that support petabyte-scale data lakes.
- Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse Analytics, Databricks Delta Lake, Oracle Autonomous Data Warehouse: Cloud data warehouses and data lakehouse platforms.
What makes Big Data testing so challenging?
Big Data testing isn’t just bigger, it’s harder. Traditional database QA methods often fall short. And Big Data testing requires experienced engineers and purpose-built validation tools.
Top Big Data Testing Challenges
- Overwhelming volume of data
- Complex testing across mixed data formats
- Limited effectiveness of traditional SQL-based testing (i.e., Minus Queries)
- Compatibility issues with Hadoop (HQL) and security tools like Kerberos
- Need for specialized test environments (like HDFS, distributed compute)
Why use QuerySurge to validate/test Big Data?
QuerySurge is built for the scale, complexity, and velocity of big data environments. Traditional testing tools and manual checks break down when you’re dealing with billions of rows, distributed processing, and constantly changing pipelines.
Why Is QuerySurge the right fit?
- Handles massive data volumes. Big Data platforms process huge datasets. QuerySurge is designed to test those datasets in parallel, compare millions or billions of records, and return precise row and column-level differences
- Validates the entire pipeline. Big Data architectures involve multiple hops: ingestion, staging, transformations, aggregations, machine learning prep, and reporting. QuerySurge tests each stage so you know data is correct before it moves forward.
- Automates at scale. Big Data pipelines need constant, repeatable testing. QuerySurge integrates with your CI/CD and DataOps workflows so you can run validations on every load, every commit, or overnight at full scale with no manual effort.
Take Control of Your Data Quality
Don’t let hidden data defects erode your analytics.
Let us show you how to detect issues before they hit your BI reports.