Open Source Analytics Apps
Discover open source analytics software that collects, visualizes, and interprets data. Boost decision‑making with dashboards, and predictive insights.
Apps in Analytics
Language
License
Arize Phoenix
Analytics · Devops · Monitoring
Open-source AI observability platform for tracing, evaluating, and debugging LLM applications with built-in intelligence and MCP support.
PostHog
Ab Testing Experimentation · Analytics · Developer Tools
The all-in-one open source product platform combining analytics, session replay, feature flags, error tracking, AI observability, and a built-in data warehouse in a single self-hostable stack.
SigNoz
Analytics · Monitoring
Self-host your entire observability stack — logs, metrics, traces, and LLM monitoring — in one OpenTelemetry-native platform, without the Datadog bill.
Checkmate
Analytics · Devops · Monitoring
Self-hosted uptime and infrastructure monitoring with multi-protocol checks, global geo-coverage, and beautiful real-time dashboards.
evidence
Analytics · Data Engineering
Turn SQL queries and markdown files into polished, interactive data apps and business intelligence reports — no drag-and-drop, no GUI, just code.
OpenReplay
Analytics
Self-hosted session replay and product analytics suite that lets you see exactly what users do on your web app — without sending data to third parties.
QuestDB
Analytics · Databases
A high-performance, open-source time-series database built for financial market data, IoT telemetry, and real-time analytics, combining a zero-GC Java/C++ core with SIMD-accelerated SQL and a WAL-to-Parquet storage engine.
Redash
Analytics · Data Engineering
Redash lets anyone connect to 35+ SQL and NoSQL data sources, write a query in the browser, and turn the result into a shared dashboard — no separate BI suite required.
WrenAI
AI Agents · Analytics · Data Engineering
Open-source GenBI engine that lets AI agents turn natural-language questions into governed SQL, charts, and shareable dashboards across 20+ data sources — no vendor lock-in, no black-box prompts.
OpenObserve
Analytics · Devops · Monitoring
Open source observability platform for logs, metrics, traces, and real user monitoring — delivering 140x lower storage costs than Elasticsearch with a single binary you can run in under 2 minutes.
HyperDX
Analytics · Developer Tools · Monitoring
Open source observability platform that unifies logs, traces, metrics, and session replays on ClickHouse — now the core of ClickStack.
ParadeDB
Analytics · Databases · Search
Born out of Y Combinator's S2023 batch, ParadeDB is a Postgres extension that delivers Elasticsearch-quality BM25 search and real-time analytics without a separate search cluster to manage.
Wakapi
Analytics · Developer Tools
Self-hosted WakaTime-compatible coding statistics backend that gives developers full control over their coding activity data.
Coroot
Analytics · Monitoring
eBPF-powered observability with AI root cause analysis — zero code changes required, full-stack visibility out of the box.
Elementary
Analytics · Data Engineering · Monitoring
The dbt-native data observability CLI that turns your existing dbt tests and metadata into anomaly detection, lineage graphs, and Slack/Teams alerts — no separate platform required.
About Analytics
Analytics software empowers businesses and developers to transform raw data into actionable insights. This category includes business intelligence dashboards, real‑time monitoring tools, data visualization libraries, event tracking platforms, and predictive analytics engines. Popular examples range from open‑source charting frameworks like Chart.js to full‑stack solutions such as Tableau, Google Analytics, and Apache Superset.
Typical use cases cover performance monitoring (e.g., server metrics or app usage), sales & marketing analysis (conversion funnels, cohort tracking), product telemetry (feature adoption, error rates), and advanced forecasting (sales predictions, churn modeling). By aggregating data from APIs, databases, logs, or third‑party services, analytics apps help teams identify trends, spot anomalies, and make data‑driven decisions faster.
For developers, integrating analytics means adding value without reinventing the wheel—whether embedding a custom dashboard, exporting metrics to a time‑series database, or leveraging machine‑learning models for predictive insights. End users benefit from clear visual reports, automated alerts, and deeper understanding of their own behavior, ultimately leading to improved performance, higher ROI, and smarter product strategies.