Open Source Analytics Apps

Discover open source analytics software that collects, visualizes, and interprets data. Boost decision‑making with dashboards, and predictive insights.

65 apps available

Apps in Analytics

Python
49%
Other

Arize Phoenix

Analytics · Devops · Monitoring

11,976

Open-source AI observability platform for tracing, evaluating, and debugging LLM applications with built-in intelligence and MCP support.

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92
Repo Health
88
Technical
67
Dependency
Built with
Python 49%
TypeScript 43%
Updated 1 weeks ago
Python
55%
Other

PostHog

Ab Testing Experimentation · Analytics · Developer Tools

40,397

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.

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92
Repo Health
80
Technical
65
Dependency
Built with
Python 55%
TypeScript 36%
Updated 1 weeks ago
TypeScript
50%
Other

SigNoz

Analytics · Monitoring

32,429

Self-host your entire observability stack — logs, metrics, traces, and LLM monitoring — in one OpenTelemetry-native platform, without the Datadog bill.

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92
Repo Health
83
Technical
64
Dependency
Built with
TypeScript 50%
Go 38%
Updated 1 weeks ago
TypeScript
98%
AGPL 3.0

Checkmate

Analytics · Devops · Monitoring

10,978

Self-hosted uptime and infrastructure monitoring with multi-protocol checks, global geo-coverage, and beautiful real-time dashboards.

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91
Repo Health
82
Technical
67
Dependency
Built with
TypeScript 98%
Updated 1 weeks ago
TypeScript
82%
MIT

evidence

Analytics · Data Engineering

7,052

Turn SQL queries and markdown files into polished, interactive data apps and business intelligence reports — no drag-and-drop, no GUI, just code.

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91
Repo Health
79
Technical
64
Dependency
Built with
TypeScript 82%
Svelte 17%
Updated 1 weeks ago
TypeScript
54%
Other

OpenReplay

Analytics

13,042

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.

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91
Repo Health
77
Technical
66
Dependency
Built with
TypeScript 54%
Go 13%
Updated 1 weeks ago
Java
93%
Apache 2.0

QuestDB

Analytics · Databases

17,466

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.

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91
Repo Health
86
Technical
67
Dependency
Built with
Java 93%
Updated 1 weeks ago
Python
45%
Other

Redash

Analytics · Data Engineering

28,849

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.

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91
Repo Health
74
Technical
61
Dependency
Built with
Python 45%
JavaScript 29%
TypeScript 19%
Updated 1 weeks ago
Python
66%
Apache 2.0

WrenAI

AI Agents · Analytics · Data Engineering

17,958

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.

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91
Repo Health
91
Technical
68
Dependency
Built with
Python 66%
Rust 31%
Updated 1 weeks ago
TypeScript
39%
AGPL 3.0

OpenObserve

Analytics · Devops · Monitoring

22,475

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.

View details
90
Repo Health
9
Technical
68
Dependency
Built with
TypeScript 39%
Rust 30%
Vue 17%
Updated 1 weeks ago
TypeScript
97%
MIT

HyperDX

Analytics · Developer Tools · Monitoring

9,963

Open source observability platform that unifies logs, traces, metrics, and session replays on ClickHouse — now the core of ClickStack.

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89
Repo Health
83
Technical
64
Dependency
Built with
TypeScript 97%
Updated 1 weeks ago
Rust
85%
AGPL 3.0

ParadeDB

Analytics · Databases · Search

9,436

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.

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89
Repo Health
87
Technical
68
Dependency
Built with
Rust 85%
PLpgSQL 15%
Updated 1 weeks ago
Go
79%
MIT

Wakapi

Analytics · Developer Tools

4,462

Self-hosted WakaTime-compatible coding statistics backend that gives developers full control over their coding activity data.

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89
Repo Health
77
Technical
72
Dependency
Built with
Go 79%
HTML 11%
Updated 1 weeks ago
Go
63%
Apache 2.0

Coroot

Analytics · Monitoring

7,982

eBPF-powered observability with AI root cause analysis — zero code changes required, full-stack visibility out of the box.

View details
88
Repo Health
80
Technical
66
Dependency
Built with
Go 63%
Vue 35%
Updated 1 weeks ago
HTML
84%
Apache 2.0

Elementary

Analytics · Data Engineering · Monitoring

2,428

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.

View details
88
Repo Health
75
Technical
75
Dependency
Built with
HTML 84%
Python 16%
Updated 1 weeks ago

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.

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