Compare DataBuck vs. RightData

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.

RightData is a versatile and user-friendly suite designed for data testing, reconciliation, and validation, enabling stakeholders to effectively pinpoint discrepancies in data consistency, quality, completeness, and existing gaps. This solution empowers users to analyze, design, construct, execute, and automate various reconciliation and validation scenarios without needing any programming skills. By identifying data issues in production, it aids in mitigating compliance risks, preserving credibility, and reducing financial exposure for organizations. RightData aims to enhance the overall quality, reliability, consistency, and completeness of your data. Additionally, it streamlines test cycles, thereby lowering delivery costs through the facilitation of Continuous Integration and Continuous Deployment (CI/CD). Furthermore, it automates the internal data audit processes, which not only broadens coverage but also boosts the audit readiness confidence within your organization, ensuring that you remain well-prepared for any compliance evaluations. Ultimately, RightData serves as a comprehensive solution for organizations seeking to optimize their data management processes and maintain high standards of data integrity.