12 Repos
Specialized storage and analysis engines for capturing and visualizing request flows across services.
Distinguishing note: Focuses on the backend storage and indexing of trace data rather than the tracing instrumentation.
Explore 12 awesome GitHub repositories matching data & databases · Distributed Tracing Backends. Refine with filters or upvote what's useful.
SigNoz is a full-stack observability platform designed to collect, store, and visualize metrics, logs, and distributed traces in a unified environment. It leverages OpenTelemetry-based data collection to ingest telemetry from diverse sources using vendor-neutral protocols, ensuring interoperability across complex microservices architectures. The platform utilizes a high-performance columnar storage engine to enable rapid aggregation and filtering, providing a centralized backend for monitoring application health and performance. What distinguishes the platform is its focus on automated instru
Captures, indexes, and visualizes request flows across complex microservice architectures.
Jaeger is a distributed tracing platform used for collecting, storing, and visualizing request flows across microservices. It identifies performance bottlenecks and errors by tracking requests as they move through multiple service boundaries. The system includes telemetry collectors, a multi-tenant backend, and a trace visualizer. The platform provides a multi-tenant tracing infrastructure that isolates data and queries by tenant to support shared environments. It supports standardized telemetry ingestion via the OpenTelemetry Protocol over gRPC and HTTP. To manage storage costs and overhead,
Provides specialized storage and analysis engines for capturing and visualizing request flows across microservices.
Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network
Directs incoming logs, metrics, or traces to specific destinations based on prioritized user-defined rules.
Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut
Directs trace spans to specific storage nodes based on service identifiers to organize AI application activity.
VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct
Orchestrates multi-node clusters to ingest, store, and query distributed trace data.
Pinpoint is a distributed application performance management tool designed to trace requests and monitor metrics across large-scale distributed architectures. It functions as a request tracer, topology mapper, and JVM application monitor, providing a backend capable of collecting and visualizing trace data from OpenTelemetry compatible sources. The system distinguishes itself through a combination of bytecode-based instrumentation via a Java agent and topology-based visualization that renders live maps of service interconnections. It captures execution flow across asynchronous boundaries, suc
Provides a backend for storing and analyzing distributed trace data from compatible sources.
NLog is an open-source logging framework for .NET that functions as a structured logging library and log routing engine. It captures log events with named parameters as searchable data rather than plain text and directs these messages to various output destinations based on severity and source. The framework is designed as an extensible platform, supporting custom targets, layout renderers, and filters that can be loaded from external assemblies or defined in code. It features a dynamic configuration system that allows logging targets, rules, and layouts to be updated via XML or programmatic
Writes log entries to trace listeners to integrate with existing tracing infrastructure.
GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without
Directs Jaeger API queries to user-specified trace tables via HTTP headers, supporting multi-table trace storage.
Cortex is an open-source, horizontally scalable metrics platform that ingests, stores, and queries Prometheus-compatible time-series data with multi-tenant isolation. It accepts metrics via Prometheus remote write and OpenTelemetry, executes PromQL queries against both recent and historical data, and provides a Prometheus-compatible alerting and recording rule engine with an integrated Alertmanager. The system is built as a set of independently scalable microservices that use hash-ring-based sharding, gossip-based cluster membership, and tenant-aware object storage to distribute workloads acro
Sets the backend for distributed tracing of requests across Cortex components.
Grafana Tempo is a high-scale distributed tracing backend and columnar trace database. It serves as an observability data store that persists and queries spans and traces using OpenTelemetry standards, allowing for the analysis of request flows across microservices. The system distinguishes itself by using an object-store based backend with columnar Parquet storage. This architecture enables efficient attribute searching and large-scale data retrieval through dedicated attribute columnization and block-based data partitioning. It includes a specialized TraceQL query engine for filtering trace
Persists trace data from services to reconstruct and visualize request flows across a distributed system.
The OpenTelemetry .NET SDK is a set of libraries used to generate and export traces, metrics, and logs from .NET applications. It functions as an application performance monitoring tool and a distributed tracing implementation, providing the necessary infrastructure to capture system metrics and request paths across microservices. The project includes a zero-code instrumentation library that automatically captures telemetry from popular .NET frameworks without requiring manual changes to source code. It uses a provider-based API abstraction to decouple instrumentation from specific backend im
Forwards observability data from multiple sources to various open source or commercial backends based on rules.
Alloy is a clustered telemetry collector and observability data pipeline that functions as an OpenTelemetry collector distribution. It acts as a declarative configuration engine for collecting and routing metrics, logs, traces, and profiles from various sources to monitoring backends. The system distinguishes itself through a distributed architecture that uses consistent hashing to balance scraping targets and collection workloads across multiple nodes. It manages fleet-wide settings via remote configuration fetching and a modular system for importing reusable pipeline patterns. As a Kubernet
Implements mechanisms for directing metrics, logs, and traces to specific destinations based on conditional rules.