Apache Griffin
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What is Apache Griffin?
Apache Griffin is an open-source data quality solution that provides a unified process to measure and improve data quality. It is commonly used to define data quality metrics, measure the accuracy and completeness of data, and monitor data quality over time. It supports various data sources and processing engines, making it a versatile tool for ensuring data reliability and trustworthiness.
What other technologies are related to Apache Griffin?
Apache Griffin Competitor Technologies
Deequ
Deequ is a library built on top of Apache Spark for defining and verifying data quality metrics, thus competing in the data quality space.
Expectations
Expectations focuses on data quality testing and validation, which is a competitive space with Apache Griffin.
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Apache Griffin Complementary Technologies
Data Lake Infrastructure
No summary available
Data Lake Infrastructure provides the storage and processing capabilities that Apache Griffin can leverage to perform data quality assessments. Apache Griffin needs access to the data to perform data quality checks.
Azure Synapse
Azure Synapse is a data warehouse and analytics service. Apache Griffin can be used to validate the data quality within Azure Synapse pipelines.
PySpark
PySpark is the Python API for Apache Spark. Griffin may use Spark, or work with data in Spark, so PySpark can be used for that.
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Which job functions commonly mention Apache Griffin?
DataOps Engineer
0.4% of all DataOps Engineer jobs mention Apache Griffin
View 38
jobs on Sumble
Data Engineer
0.1% of all Data Engineer jobs mention Apache Griffin
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jobs on Sumble
Data Architect
11 Data Architect jobs mention Apache Griffin
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jobs on Sumble
Software Engineer
278 Software Engineer jobs mention Apache Griffin
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jobs on Sumble
Data, Analytics & Machine Learning
33 Data, Analytics & Machine Learning jobs mention Apache Griffin
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jobs on Sumble
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