digna vs Objectiv
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Open-source product analytics infrastructure with a generic event taxonomy, so models built on one company's data set can be deployed and run on another. | Is the game-changing European modern data quality platform that effortlessly uncovers anomalies and errors in your data with Artificial Intelligence. |
Collect validated user behavior data with a generic event structure;
Feed it into your data warehouse;
Model on the raw data without cleaning & transformation;
Take & run pre-built models off the shelf;
Reuse and share any model between teams, products and platforms;
Use pandas-like operations that run on the full SQL dataset;
Convert models to SQL with one command, to feed all data consumers from a single source of truth;
Self-hosted and free to use. | data validation, BCBS 239 data quality, regulatory data observability, banking data governance, risk reporting data quality, risk aggregation, manipulation anomaly indicators, data lineage insights, data SLA monitoringschema monitoring, schema change detection, new column detection, removed column detection, datatype change detection, schema drift detection, database schema tracking, schema observabilitydata freshness monitoring, data timeliness, late data detection, missing batch detection, data arrival monitoring, delivery timestamp tracking, trigger-based timestamp, SQL-derived timestamp, pipeline latency monitoring, SLA breach alertstimeliness, schema tracker, data analytics, prebuilt data quality rules, 9000+ rules, custom data rules, SQL validation rules, rule engine, conditional data rules, uniqueness checks, range checks, primary key validation, cross-table validation, rule exceptions, severity levelsproject management, trend analysis, time-series analytics, volatility detection, change point detection, long-term data trends, stable dataset detection, unstable dataset detection, pattern recognition, historical data metrics, data profiling analyticsworkspace managementAI anomaly detection, data anomalies, volume anomalies, distribution anomalies, outlier detection, data drift detection, missing values detection, NULL pattern analysis, threshold monitoring, detect data manipulation, early warning signals, automatic anomaly detection, Slack alerts, email alerts, Teams alerts, webhook alerts, role-based access control, RBAC, scheduling inspections, cron scheduling, event-based scheduling, CLI access, API access, SSO integration, OIDC, Microsoft SSO, Google SSO, multi-database connectors, on-prem installation, private cloud installation, secure deployment |
Statistics | |
GitHub Stars 464 | GitHub Stars - |
GitHub Forks 40 | GitHub Forks - |
Stacks 3 | Stacks 1 |
Followers 6 | Followers 2 |
Votes 0 | Votes 2 |
Integrations | |
| No integrations available | |
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