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
Okyline
Okyline is an Executable Data Design (EDD) platform focused on executable validation contracts and operational data quality control.
Rather than managing separate specifications, validation code, tests, and monitoring dashboards, Okyline centralizes validation and quality supervision around a single readable executable contract acting as the operational reference for enterprise data flows.
The same contract powers deterministic validation, advanced business invariant checks, multi-format execution, data quality gates, and historical quality analytics across APIs, events, files, LLM structured outputs, and distributed operational systems.
Contracts are designed directly from annotated sample data, making validation rules immediately understandable for developers, architects, QA teams, and business analysts.
The Community Edition includes the public specification, a free Java runtime engine, a Claude AI assistant for contract generation, and an online studio supporting executable JSON validation contracts and JSON Schema transpilation.
The Enterprise Edition adds native validation for JSONL, XML, CSV, FIXED, and EDI flows together with operational quality dashboards and data quality gates, without requiring databases or centralized infrastructure.erprise Edition supports direct validation of JSON, JSONL, XML, CSV, FIXED, and EDI flows with operational quality dashboards and analytics, without databases.
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RaimaDB
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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Cloudera DataFlow
Cloudera DataFlow for the Public Cloud (CDF-PC) is a versatile, cloud-based data distribution solution that utilizes Apache NiFi, enabling developers to seamlessly connect to diverse data sources with varying structures, process that data, and deliver it to a wide array of destinations. This platform features a flow-oriented low-code development approach that closely matches the preferences of developers when creating, developing, and testing their data distribution pipelines. CDF-PC boasts an extensive library of over 400 connectors and processors that cater to a broad spectrum of hybrid cloud services, including data lakes, lakehouses, cloud warehouses, and on-premises sources, ensuring efficient and flexible data distribution. Furthermore, the data flows created can be version-controlled within a catalog, allowing operators to easily manage deployments across different runtimes, thereby enhancing operational efficiency and simplifying the deployment process. Ultimately, CDF-PC empowers organizations to harness their data effectively, promoting innovation and agility in data management.
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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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Pricing
Pricing Starts At:
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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
DataOps DataFlow Features and Options
Data Management Software
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
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