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Guzzle: Workbench for Data Engineering & Science

GUZZLE – is a Spark Native workbench for data scientists and data engineers to productionize their data pipelines at scale. Released under the Apache 2.0 license, Guzzle can natively handle diverse workloads (batch, streaming, real-time and API) and uses a declarative framework and UI to build production quality pipelines with agile timelines. Native DevOps integration, with audit and governance controls bolsters rapid development sprints to fast-tracked delivery cycles, with the quality controls of a production deployment.

 

Guzzle can help you with:

Data Ingestion

Data Ingestion

Config as code governed ingestion & processing capabilities from File, Database, HDFS, DBFS
Job orchestration

Job orchestration

Native integration with Azure Data Factory for orchestration & Apache Atlas for governance
Runtime audit

Runtime audit

Detailed run-time audit and statistics including row counts, statistics and dependencies
Constraint Check

Constraint Check

Automated critical data element monitoring and exception alerting, with detailed link to failed records
Traceability and Recon

Traceability and Recon

Automated reconciliation between source and target, with data traceability across multiple steps.
Housekeeping

Housekeeping

Automated management of historical snapshots and retention compliance
Data Sources

Data Lake Without Guzzle

Before Guzzle

Data Lake With Guzzle

After Guzzle
Insights
Data Lake Without Guzzle
Data Lake With Guzzle
Data Sources
Before Guzzle
After Guzzle
Insights

Make the most of your Data

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