digna vs Snowplow
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Snowplow is a real-time event data pipeline that lets you track, contextualize, validate and model your customers’ behaviour across your entire digital estate. | Is the game-changing European modern data quality platform that effortlessly uncovers anomalies and errors in your data with Artificial Intelligence. |
Track rich events from your websites, mobile apps, server-side systems, third party systems and any type of connected device, so that you have a record of what happened, when, and to whom;Load your data into your data warehouse of choice to power sophisticated analytics;Process your data including validating, enriching and modeling it;Your data is available in real-time via Amazon Kinesis, Google Pub/Sub and BigQuery to power real-time applications and reports;Your data pipeline is running in your cloud environment giving you full ownership and control of your data | 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 7.0K | GitHub Stars - |
GitHub Forks 1.2K | GitHub Forks - |
Stacks 133 | Stacks 1 |
Followers 174 | Followers 2 |
Votes 35 | Votes 2 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
| No integrations available | |
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