rudderlabs/rudder-server
Rudder Server
Rudder Server is a customer data platform and event routing pipeline designed to collect, transform, and route customer event data from various sources to data warehouses and business tools. It functions as a customer identity resolver, linking identifiers from multiple sources to build a unified identity graph and comprehensive behavioral customer profiles.
The system differentiates itself through reverse ETL capabilities, which push processed customer segments and audiences from data warehouses back into operational third-party applications. It also provides a containerized data plane for Kubernetes deployments, enabling the management of data infrastructure as code.
The platform covers a broad range of data management capabilities, including real-time event transformation, schema validation via data catalogs, and privacy governance. These include tools for managing user consent, enforcing data residency within specific geographic regions, and masking personally identifiable information during flight.
Installation and deployment of the data plane components are managed using Helm charts.
Features
- Customer Data Pipelines - Streams and routes customer information from applications and websites to analytics tools and warehouses.
- Customer Data Platforms - Functions as a complete platform for collecting, routing, and transforming customer event data to warehouses and tools.
- Multi-Destination Event Routing - Routes a single stream of event data to multiple external analytics destinations via a unified interface.
- Reverse ETL - Synchronizes processed customer segments from data warehouses back into operational third-party applications.
- Customer Profiles - Resolves identifiers across multiple sources to build an identity graph and behavioral customer profiles.
- Customer Identity Resolution - Links identifiers from multiple sources to build a unified identity graph without manual queries.
- Unified Customer Profiles - Aggregates event data within warehouses to build comprehensive, centralized views of each customer.
- Automatic Event Collection - Gathers standardized events from web, mobile, and server-side sources using SDKs and webhooks.
- Customer Data Routing - Collects events from applications and websites and pipes them into data warehouses and business tools.
- Customer Identity Resolution - Builds a unified identity graph by linking identifiers from multiple sources to create comprehensive customer profiles.
- Data Catalogs - Provides a central catalog to define events and manage tracking plans to block malformed data.
- Streaming Data Cleaning & Enrichment - Cleans, enriches, and masks personally identifiable information within events as they move through the pipeline.
- Data Format Transformations - Converts event data into destination-specific formats using a pipeline of enrichment, filtering, and anonymization functions.
- Event-Driven Data Pipelines - Implements a reactive system to process, filter, and transform live event streams before delivery.
- Data Quality Frameworks - Enforces schema validation and consent automation to ensure high data reliability before delivery.
- Data Transformation Rules - Applies real-time filtering, masking, and enrichment logic to events before they reach the destination.
- Data Warehouse Exporters - Provides connectors to stream and batch event data directly into cloud-based data warehouses.
- Event Data Ingestion - Processes and collects customer interaction events from various sources to feed into a centralized pipeline.
- Reverse ETL Synchronizations - Implements reverse ETL to push processed customer segments and audiences from warehouses back into operational business tools.
- Event Ingestion Pipelines - Ingests customer data events through a web interface to route information into a data pipeline.
- Tracking Plan Coordination - Monitors incoming event data against predefined schemas in a central catalog to block malformed data.
- Reverse ETL Tools - Pushes processed customer segments and audiences from data warehouses back into operational third-party applications.
- Consent Management - Captures and tracks user privacy preferences to ensure compliance with global data regulations.
- Event Data Governance - Provides governance for event data including consent collection and data subject requests for privacy compliance.
- Data Privacy Controls - Restrict which specific pieces of customer data are forwarded to analytical tools to maintain security and privacy.
- Data Privacy Regulation Compliance - Handles identity removal and data suppression requests across storage to comply with global privacy regulations.
- Data Residency Controls - Processes and stores event data within specific geographic regions to ensure regulatory data residency compliance.
- Event Schema Validators - Checks incoming events against a central tracking plan to block malformed data and ensure quality.
- Identity Linking - Links disparate identifiers from multiple sources to build a unified identity graph and customer profiles.
- Third-Party Application Integrations - Integrates with a variety of marketing, analytics, and operational business tools to deliver customer event data.
- Pipeline Resource Management - Provides programmatic control over the creation and configuration of data collection pipelines and connection resources.
- Customer Data Applications - Runs attribution, propensity scoring, and real-time personalization logic using customer profile data.
- Data Enrichment - Adds geolocation and additional context to events during pipeline processing to improve data quality.
- Warehouse Schema Provisioning - Automatically creates target table structures in destination warehouses based on incoming event data.
- Event Filtering Rules - Blocks or permits specific events from reaching destinations based on configurable rules and consent requirements.
- Event Relays - Receives event data from applications and relays it to specified warehouses or business tools.
- Infrastructure as Code Deployments - Enables deployment and management of data pipelines using containerized infrastructure as code.
- Infrastructure as Code - Allows the data stack to be managed as code via programmatic interfaces and CLI tools for version-controlled deployments.
- Helm Chart Deployments - Supports installation and management of the data plane components on Kubernetes using Helm charts.
- Kubernetes Data Planes - Provides a containerized data plane managed via Helm charts for scalable event ingestion.
- Real-Time Event Handlers - Provides application logic to trigger personalized actions for users immediately based on incoming event data.
- Delivery Guarantees - Ensures event delivery during destination downtime using a persistent retry mechanism and error handling.
- Destination Integration Plugins - Provides a standardized plugin system for delivering data to various third-party warehouses and business tools.
- Gateway Performance Monitoring - Tracks delivery latency, event counts, and error rates across gateway and router stages.
- Pipeline Health Monitors - Tracks pipeline state and event flows to identify and debug data delivery issues.
- Metric and Performance Monitors - Provides a centralized view of key delivery metrics and data pipeline performance.
- Visual Data Pipeline Builders - Ships a visual user interface for building and controlling connections between event data sources and destinations.
- Analytics Platforms - Privacy-focused data pipeline and segment alternative.
- Analytics Tools - Listed in the “Analytics Tools” section of the Awesome Selfhosted awesome list.
- Data Ingestion - Open-source customer data infrastructure for event routing.
- Data Ingestion Pipelines - Open-source customer data infrastructure for event streaming.
- Data Pipelines - Open-source customer data infrastructure.
- Workflow Orchestration - Customer data platform for collecting and activating warehouse data.
