iceDQ
iceDQ is the #1 data reliability platform offering powerful, unified capabilities for Data Testing, Data Monitoring, and Data Observability. Designed for modern data environments, iceDQ automates complex data pipelines and data migration testing to ensure accuracy, integrity, and trust in your data systems. Its AI-based observability engine continuously monitors data in real-time, quickly detecting anomalies and minimizing business risks.
With robust cross-platform connectivity, iceDQ supports seamless data validation, data profiling, and data reconciliation across diverse sources — including databases, files, data lakes, SaaS applications, and cloud environments. Whether you're migrating data, ensuring ETL/ELT process quality, or monitoring live data streams, iceDQ helps enterprises deliver high-quality, reliable data at scale. From financial services to healthcare and beyond, organizations rely on iceDQ to make confident, data-driven decisions backed by trusted data pipelines.
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DataLark
DataLark is an SAP-centric no-code / low-code data management platform that helps businesses streamline data migration, data maintenance, and integration processes. Using its customizable plugins and analytical tools, you can automate all ETL operations and orchestrate across all of your systems to drive better business decisions.
DataLark's rapid deployment allows you to launch your data-related processes within hours with the help of live support and extensive documentation.
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DQOps
DQOps is an open-source data quality platform designed for data quality and data engineering teams that makes data quality visible to business sponsors.
The platform provides an efficient user interface to quickly add data sources, configure data quality checks, and manage issues. DQOps comes with over 150 built-in data quality checks, but you can also design custom checks to detect any business-relevant data quality issues. The platform supports incremental data quality monitoring to support analyzing data quality of very big tables. Track data quality KPI scores using our built-in or custom dashboards to show progress in improving data quality to business sponsors.
DQOps is DevOps-friendly, allowing you to define data quality definitions in YAML files stored in Git, run data quality checks directly from your data pipelines, or automate any action with a Python Client. DQOps works locally or as a SaaS platform.
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DataTrust
DataTrust is built to accelerate test cycles and reduce the cost of delivery by enabling continuous integration and continuous deployment (CI/CD) of data. It’s everything you need for data observability, data validation, and data reconciliation at a massive scale, code-free, and easy to use. Perform comparisons, and validations, and do reconciliation with re-usable scenarios. Automate the testing process and get alerted when issues arise. Interactive executive reports with quality dimension insights. Personalized drill-down reports with filters. Compare row counts at the schema level for multiple tables. Perform checksum data comparisons for multiple tables. Rapid generation of business rules using ML. Flexibility to accept, modify, or discard rules as needed. Reconciling data across multiple sources. DataTrust solutions offers the full set of applications to analyze source and target datasets.
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