digna vs Snowplow
Overview
🔥 Trending in Analytics on StackShare
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 130 | Stacks 1 |
Followers 174 | Followers 2 |
Votes 35 | Votes 2 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
| No integrations available | |
What are some alternatives to Snowplow, digna?
Keen
Keen is a powerful set of API's that allow you to stream, store, query, and visualize event-based data. Customer-facing metrics bring SaaS products to the next level with acquiring, engaging, and retaining customers.
Zustand
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Quickmetrics
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Statsbot
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Ahoy
Ahoy provides a solid foundation to track visits and events in Ruby, JavaScript, and native apps.
Bitdeli
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Sportlingo
AI-powered sports analytics and skill assessment API that enables apps and platforms to deliver personalized training, drills, and performance insights.
Open Web Analytics
It is open source web analytics software that you can use to track and analyze how people use your websites and applications. It provides website owners and developers with easy ways to add web analytics to their sites using simple Javascript, PHP, or REST based APIs.
Iteratively
Iteratively helps teams capture reliable product analytics they can trust. It eliminates the most common causes of error during the definition and implementation of tracking plans, and cuts down on the time it takes to correctly instrument the product. As a result, folks that consume product analytics get exactly what they spec'd out and can rely on the incoming data knowing it is trustworthy and accurate.
Objectiv
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.
