DataOps DataFlow Description
Apache Spark provides a holistic component-based platform to automate Data Reconciliation tests for modern Data Lake and Cloud Data Migration Projects.
DataOps DataFlow provides a modern web-based solution to automate the testing of ETL projects, Data Warehouses, and Data Migrations. Use Dataflow to load data from a variety of data sources, compare the data, and load differences into S3 or a Database. Create and run dataflow quickly and easily. A top-of-the-class testing tool for Big Data Testing
DataOps DataFlow integrates with all modern and advanced sources of data, including RDBMS and NoSQL databases, Cloud and file-based.
DataOps DataFlow Alternatives
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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QuerySurge
QuerySurge is the smart Data Testing solution that automates the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Applications with full DevOps functionality for continuous testing.
Use Cases
- Data Warehouse & ETL Testing
- Big Data (Hadoop & NoSQL) Testing
- DevOps for Data / Continuous Testing
- Data Migration Testing
- BI Report Testing
- Enterprise Application/ERP Testing
Features
Supported Technologies - 200+ data stores are supported
QuerySurge Projects - multi-project support
Data Analytics Dashboard - provides insight into your data
Query Wizard - no programming required
Design Library - take total control of your custom test desig
BI Tester - automated business report testing
Scheduling - run now, periodically or at a set time
Run Dashboard - analyze test runs in real-time
Reports - 100s of reports
API - full RESTful API
DevOps for Data - integrates into your CI/CD pipeline
Test Management Integration
QuerySurge will help you:
- Continuously detect data issues in the delivery pipeline
- Dramatically increase data validation coverage
- Leverage analytics to optimize your critical data
- Improve your data quality at speed
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Datagaps DataOps Suite
The Datagaps DataOps Suite serves as a robust platform aimed at automating and refining data validation procedures throughout the complete data lifecycle. It provides comprehensive testing solutions for various functions such as ETL (Extract, Transform, Load), data integration, data management, and business intelligence (BI) projects. Among its standout features are automated data validation and cleansing, workflow automation, real-time monitoring with alerts, and sophisticated BI analytics tools. This suite is compatible with a diverse array of data sources, including relational databases, NoSQL databases, cloud environments, and file-based systems, which facilitates smooth integration and scalability. By utilizing AI-enhanced data quality assessments and adjustable test cases, the Datagaps DataOps Suite improves data accuracy, consistency, and reliability, positioning itself as a vital resource for organizations seeking to refine their data operations and maximize returns on their data investments. Furthermore, its user-friendly interface and extensive support documentation make it accessible for teams of various technical backgrounds, thereby fostering a more collaborative environment for data management.
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Pricing
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Pricing Information:
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Integrations
Company Details
Company:
Datagaps
Year Founded:
2010
Headquarters:
United States
Website:
www.datagaps.com/dataops-dataflow/
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Product Details
Platforms
Windows
Mac
Linux
Customer Support
Business Hours
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