Social Analyzer scans over 1,000 social media platforms in parallel to discover and correlate user profiles from a single username query, making it the most comprehensive OSINT reconnaissance tool of its kind. Three detection modes cover different accuracy and speed tradeoffs: fast HTTP library checks for rapid sweeps, Selenium WebDriver validation for JavaScript-heavy sites, and a special mode for stubborn edge cases. String analysis generates username permutations and combinations to catch related accounts with slight naming variations. Three interfaces serve different workflows: a Node.js web application on port 9005 with a browser-based GUI, a CLI for scripted batch operations, and Python plus Node.js APIs for embedding into automated investigation pipelines. The QeeqBox OSINT library extracts profile metadata, screenshots, titles, descriptions, and activity patterns, all visualized through Ixora-based force-directed graphs that map relationships between discovered accounts. Tesseract OCR analyzes profile images for additional detection vectors. Search results narrow by country codes, website categories, Alexa ranking thresholds, and confidence levels. Optional Google API and DuckDuckGo API integration adds search engine correlation alongside direct platform queries. Docker deployment bundles Node.js, Firefox ESR, Tesseract, and all dependencies into one container. Trusted by law enforcement and security researchers for digital forensics and identity verification. 23,000+ GitHub stars. AGPL-3.0 licensed.

GoAccess processes millions of web log entries in seconds and renders the results as interactive dashboards that update every 200 milliseconds in the terminal or every second via WebSocket-connected HTML reports. Written entirely in C with only ncurses as a dependency, it achieves exceptional performance even on resource-constrained servers, reducing memory usage by approximately 20% and parsing time by 35% in recent releases through optimized in-memory hash tables with on-disk persistence support. The analyzer parses virtually every web log format out of the box (Apache Combined and Common, Nginx, Amazon CloudFront, Amazon S3, AWS Elastic Load Balancing, Google Cloud Storage, Squid, W3C IIS, Caddy JSON, and Traefik) while supporting fully custom log format strings for non-standard configurations. The self-contained HTML dashboard displays 15+ interactive panels covering unique visitors, requested files, static files, 404 errors, referring sites, search keyphrases, geographic location with city-level GeoIP resolution, operating systems, browsers, HTTP status codes, time distribution, and virtual host metrics. WebSocket authentication via JWT provides secure remote access, and incremental log processing ensures data continuity across daemon restarts. Docker deployment requires a single command with volume-mapped access logs. Over 20,800 stars with active development since 2010. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With nearly 9,000 GitHub stars and adoption by over 60,000 companies across 100 countries, Papermark is the open-source DocSend alternative that turns document sharing into a data-rich conversation between you and your viewers. Every shared document generates page-by-page analytics showing exactly which pages capture attention, how long viewers spend on each section, where they drop off, and whether they return for a second look, with real-time notifications the moment a document is opened. Virtual data rooms support unlimited folders with drag-and-drop organization, bulk uploads, granular per-viewer permissions, dynamic watermarking that stamps each page with the viewer's identity, and NDA gating that requires agreement before access. Custom branding applies your logo, colors, and custom domain to every shared link and download page, while email verification and password protection add authentication layers. The AI Data Room Copilot lets viewers chat with uploaded documents, ask questions, and receive contextual summaries directly within the data room interface. The developer platform exposes 43 REST API operations covering data rooms, documents, folders, links, visitors, and analytics, with an MCP server for AI agent integration and a CLI for automation. Built on Next.js with TypeScript, Prisma ORM, PostgreSQL, NextAuth.js authentication, and shadcn/ui components. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

OpenSEO provides an alternative to the $100+/month SEO suite monopoly by connecting directly to DataForSEO APIs on a pay-as-you-go basis — you bring your own API key and pay only for the queries you actually make. The platform delivers focused workflows for keyword research with volume, difficulty, CPC, intent, and live SERP inspection; rank tracking with historical position monitoring; backlink analysis with referring domain quality scoring; technical site audits that crawl pages and surface issues; competitor insights comparing SERP positions across keyword sets; and AI visibility monitoring that tracks brand mentions, citations, and prompts across AI models. The integrated MCP server exposes all tools to AI coding agents including Claude Code, OpenClaw, Hermes, and Cursor, while Agent Skills provide reusable SKILL.md workflows that guide agents through complex SEO research tasks. Google Search Console integration reads first-party performance data including clicks, impressions, CTR, and position metrics with URL-level index status inspection. The Prompt Explorer compares how different AI models respond to SEO-relevant queries. Self-host via Docker for personal use or deploy to Cloudflare for team access with automatic database backups. The hosted version at openseo.so adds a 28% markup on DataForSEO requests. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Built as a direct rejection of the adtech model, Plausible is the best-known privacy-first web analytics tool - lightweight, cookie-free, and open-source. It sets no cookies and stores no personal data: unique visitors are counted via a hash of IP plus User-Agent that rotates every 24 hours and is never stored raw, so no consent banner is required and GDPR compliance is structural rather than contractual. The tracking script is under 1 KB - orders of magnitude lighter than GA - and the dashboard is a deliberate contrast to GA4's sprawl: one fast-loading page with visitors, sources, top pages, countries, devices, and UTM breakdowns, filterable by any dimension. Custom events and goals track signups and clicks, Google Search Console integration pulls in search queries, scheduled email reports keep stakeholders updated, and the Stats API (v2) plus CSV export feed data anywhere. This is the AGPL-licensed Community Edition, the same Elixir codebase that powers Plausible's cloud service, running as three containers: the web app, PostgreSQL for accounts, and ClickHouse for event storage - which means self-hosters get direct SQL access to raw analytics data the cloud version never exposes. Traffic data stays entirely on your server, with no visitor caps or per-pageview pricing.

Used by over 3,000 organizations including Dropbox, Khan Academy, Sony, Pepsi, Wikipedia, and Mistral, GrowthBook is the open-source experimentation platform that handles over 100 billion feature flag evaluations daily across its cloud and self-hosted deployments. Feature flags support advanced targeting with user attributes, gradual percentage rollouts, prerequisite dependencies, and scheduled launches, with both client and server SDKs evaluating flags locally from a cached payload for sub-millisecond performance with zero network calls per check. The warehouse-native architecture queries experiment results directly from 11 data sources including BigQuery, Snowflake, Databricks, Redshift, ClickHouse, Mixpanel, and PostgreSQL, eliminating duplicate data pipelines. The statistics engine implements CUPED variance reduction, sequential testing, Bayesian analysis, post-stratification, multi-armed bandits, and sample ratio mismatch checks with fully open-source methodology. Product analytics provides dashboards with funnels, retention cohorts, and event-based tracking shareable across teams. Twenty-four SDKs cover React, Next.js, Node.js, Python, Go, Ruby, PHP, Java/Kotlin, Swift, C#/.NET, Rust, Elixir, Angular, and edge runtimes including Cloudflare Workers, Fastly Compute, and Lambda@Edge. The MCP server and REST API enable AI coding agents to create features, start experiments, and manage stale flags programmatically. Self-hosting deploys via Docker Compose with MongoDB, or via Helm charts on Kubernetes, with the same codebase powering both open-source and managed cloud offerings. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With over 31,600 GitHub stars and thousands of production deployments, InfluxDB 3 Core is the open-source time series database rebuilt in Rust on the FDAP stack — Apache Flight for high-throughput data transfer, DataFusion for vectorized SQL query execution, Arrow for columnar in-memory representation, and Parquet for compressed columnar storage. The engine delivers sub-10ms query response times on recent data and handles millions of writes per second through line protocol ingestion over HTTP, with unlimited tag cardinality eliminating the high-cardinality limitations that plagued earlier InfluxDB versions. The diskless architecture persists data as compressed Parquet files to S3-compatible object storage, Azure Blob, Google Cloud Storage, or local disk with configurable partitioning strategies, while the write-ahead log and in-memory buffer serve real-time queries against recent data before compaction. Native SQL support through DataFusion includes window functions, CTEs, subqueries, and joins, while InfluxQL maintains backward compatibility with existing InfluxDB 1.x and 2.x applications through the same query API. The embedded Python VM enables processing engine plugins and triggers that execute custom logic on write events, perform cross-database queries, and transform data in real time without external tooling. Flight SQL clients provide high-performance query access from Python, Go, Java, and Rust, and the HTTP API supports writes in line protocol format compatible with Telegraf's 300+ input plugins. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT/Apache 2.0 dual-licensed.

With nearly 12,000 GitHub stars and a lineage tracing back to Sphinx Search, Manticore Search is the C++ search database that delivers the full-text, vector, and hybrid search capabilities of Elasticsearch at a fraction of the resource cost — starting in under a second and consuming just 40MB RAM for an empty instance. The SQL-first interface speaks the MySQL wire protocol, meaning mysql client, MySQL Workbench, and any MySQL-compatible driver connects natively without adapters, while the HTTP JSON API provides RESTful access for modern applications. Over 20 full-text operators handle proximity search, quorum matching, field-start and field-end constraints, MAYBE operators, and regex patterns, backed by stemming, lemmatization, stopwords, synonyms, wordforms, and advanced morphology in 70+ languages. Vector search with HNSW indexing enables semantic similarity queries, and hybrid mode combines keyword relevance with vector distance in a single ranked result set using a cost-based query optimizer. Real-time indexing delivers sub-second document availability after insert, sharded tables distribute data across nodes, and Galera-based synchronous replication ensures high availability. Conversational search via CREATE CHAT MODEL and CALL CHAT integrates LLM-backed responses with KNN retrieval and conversation history directly inside the database. Client libraries ship for PHP, Python, JavaScript, TypeScript, Java, Go, Rust, and Elixir. Columnar storage via the Manticore Columnar Library handles analytical workloads on large datasets. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPLv3 licensed.

Known as the open-source Mixpanel alternative that respects user privacy, OpenPanel delivers a unified web and product analytics platform combining Mixpanel's behavioral analysis with the simplicity of Plausible and full data ownership through self-hosting. Cookieless tracking eliminates consent banners entirely while still capturing events, page views, sessions, user journeys, funnels, retention cohorts, and custom properties with full GDPR compliance by design. The 2.3 KB async script loads without blocking page rendering, and 16 official SDKs cover Next.js, React, Vue, Astro, Remix, Nuxt, Angular, Svelte, React Native, Swift, Kotlin, Python, PHP, Laravel, Express, and REST API for custom integrations. Real-time dashboards display live visitor counts, active sessions, and event streams as they happen. Custom chart builders create tailored visualizations from any tracked event with breakdowns by property, time period, and user segment. Session replay reconstructs individual user journeys showing every page visited, event triggered, and interaction recorded. Funnel analysis identifies conversion drop-offs with step-by-step breakdown and property filtering. Retention analysis measures how often users return with customizable time windows and cohort comparisons. A/B testing and variant tracking enable experiment measurement directly within the platform. Event notifications alert when specific events occur or thresholds are crossed. The self-hosted deployment uses Docker Compose with ClickHouse for high-speed analytical queries, PostgreSQL for metadata, and Redis for real-time processing — deployable on any VPS or Kubernetes cluster. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Web analytics tools ignore native mobile, desktop, and game apps; Aptabase was built for exactly those. If Firebase Analytics would force a privacy-policy footnote you don't want to write, this is the alternative - session-based metrics with no cookies, no IDFA or GAID, no device fingerprinting, and a daily-rotated salt that makes cross-day re-identification mathematically impossible. That design means GDPR, CCPA, and PECR compliance out of the box and "Data Not Collected" App Store privacy labels without ATT prompts. The SDK coverage is the widest in its category: eleven first-party libraries spanning Swift, Kotlin, Flutter, React Native, Tauri, Electron, .NET MAUI, NativeScript, Unity, Unreal Engine, and JavaScript for web - each MIT-licensed, following platform conventions, and accepting a custom host parameter that points at your instance. Integration is minutes: initialize with an app key, call trackEvent with optional properties, and the dashboard shows sessions, events, app versions, OS breakdowns, and country-level geography. The self-hosted stack is a .NET server over PostgreSQL for metadata and ClickHouse for high-volume event ingestion, giving cloud-parity features under an AGPL license. For indie iOS/Android apps, Electron and Tauri tools, and Unity or Unreal games, it replaces Firebase without the Google entanglement.

Traffic analytics, real-user performance monitoring, and client-side error tracking - normally three tools - in one cookieless, privacy-first dashboard: Swetrix. The Community Edition ships the same core engine as the cloud product - a NestJS API with ClickHouse for high-volume event storage, MySQL for relational data, and Redis for caching, fronted by a React dashboard and a ~5 KB tracking script with official packages for 20+ frameworks including Next.js, WordPress, and Shopify. Traffic analytics cover pageviews, referrers, UTM campaigns, geolocation, sessions with page flows, funnels, and custom events - all anonymized server-side with no cookies, no cross-device tracking, and no consent banner required for GDPR compliance. Performance monitoring records real-user metrics per pageview: TTFB, DNS and TLS timing, and render times, so regressions surface in the same place as traffic. Error tracking captures unhandled JavaScript exceptions automatically with formatted stack traces, filename/line metadata, affected browsers and pages, first/last-seen timestamps, and a resolve workflow - replacing a separate error monitoring subscription for many teams. Alerts fire to email, Slack, Telegram, Discord, or webhooks on traffic spikes, new errors, and custom events. If Plausible covers your traffic questions but you also want to know why the site broke, Swetrix answers both.

With over 11,000 GitHub stars and now backed by Datadog while remaining fully Apache 2.0 licensed, Quickwit delivers the search performance Elasticsearch users expect at a fraction of the infrastructure cost by moving the index to object storage instead of expensive local SSDs. The Rust-based engine, built on the Tantivy search library with SIMD-accelerated vectorized processing and zero garbage collection overhead, achieves sub-second search latency directly against Amazon S3, Azure Blob Storage, Google Cloud Storage, or any S3-compatible backend like MinIO and Ceph. The Elasticsearch-compatible REST API covers ingest, search, query DSL, and aggregations, enabling existing log shippers including Vector, Fluent Bit, and Syslog to migrate without rewriting configurations. Native OpenTelemetry Protocol endpoints accept logs and traces via gRPC, while Jaeger integration provides a drop-in distributed tracing backend. Ingestion from Apache Kafka, Amazon Kinesis, and Apache Pulsar supports streaming pipelines with multi-index partitioning, and the schemaless JSON indexing mode eliminates the need for upfront schema definitions. Stateless searchers and indexers scale horizontally on Kubernetes or bare metal, with a control plane that distributes indexing tasks and a janitor that manages retention policies and GDPR-compliant deletions. The built-in web UI displays search results and cluster state, while the official Grafana data source enables log exploration dashboards. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

With 12,400 GitHub stars and adoption across enterprises processing billions of events daily, Redpanda delivers a complete Kafka wire protocol implementation in C++ that existing Kafka producers, consumers, Kafka Connect connectors, and Kafka Streams applications connect to without code changes — eliminating JVM garbage collection pauses and ZooKeeper coordination overhead through a single binary architecture built on the Seastar framework's thread-per-core model. The integrated schema registry supports Avro, Protobuf, and JSON Schema validation directly within the broker without separate infrastructure. Tiered storage automatically offloads cold data to object storage while maintaining seamless consumer access across the full retention window. Redpanda Console provides a web-based management interface for topic inspection, consumer group monitoring, schema management, and ACL configuration. Redpanda Connect extends the platform with 200+ pre-built connectors for data pipelines between databases, cloud services, and streaming systems. Exactly-once semantics with idempotent producers and transactional guarantees ensure data integrity for financial, healthcare, and compliance workloads. The Adaptable Data Plane in version 26.1 enables per-topic performance profiles balancing throughput, latency, and durability within a single cluster. Deploy via Docker or Kubernetes with official Helm charts — a three-node cluster starts with a single rpk command. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSL 1.1 licensed (converts to Apache 2.0 after four years).

Chartbrew transforms raw database queries and API responses into polished, shareable dashboards without requiring a data engineering team. Connect to MySQL, PostgreSQL, MongoDB, Firestore, or any REST API, then build datasets using the visual query editor with syntax highlighting and auto-completion. Charts render through Chart.js with line, bar, pie, donut, radar, polar, KPI card, and table visualizations, each customizable with colors, legends, filters, and goal indicators. An AI assistant accelerates dashboard creation by generating queries and suggesting chart configurations from natural language descriptions of the metrics you want to track. Reusable datasets let teams prepare data transformations once and share them across multiple charts, while automatic scheduling through BullMQ and Redis refreshes data at intervals from every 10 minutes to monthly. The embed feature generates standalone chart URLs for insertion into external websites, internal tools, or customer portals, and the Reporting API enables programmatic dashboard management and automated report delivery. Team workspaces with role-based permissions control who can view, edit, or manage data connections. Nearly 4,000 GitHub stars reflect steady community adoption. The platform runs on Node.js with Express and Sequelize ORM, supporting MySQL or PostgreSQL as its application database. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. FSL-1.1-MIT licensed (converts to MIT two years after each release).

Backed by Y Combinator (S24) and processing traces from thousands of AI agents in production, Laminar is the open-source observability platform that treats agent debugging as a first-class engineering discipline rather than an afterthought. Its OpenTelemetry-native SDK auto-instruments Vercel AI SDK, LangChain, OpenAI, Anthropic, Gemini, Browser Use, Stagehand, Mastra, Pydantic AI, and the OpenAI Agents SDK with a single line of code, capturing every LLM turn, tool call, and sub-agent delegation as nested spans with full input/output data and token costs. The Signals engine lets you describe failures in plain language — "agent is stuck in a loop" or "tool returned empty results" — then reads every trace and alerts via Slack when it detects a match. A built-in debugger records runs and replays them from cache so each iteration takes seconds, designed for Claude Code, Cursor, or Codex to drive the repair loop via the MCP server or CLI. Run code-first evaluations in Python or TypeScript locally or in CI/CD pipelines, build datasets from production traces, and query everything with raw SQL through custom dashboards, the in-app editor, or your coding agent. The Rust backend delivers 20x trace compression, a custom real-time streaming engine, ultra-fast full-text search, and gRPC ingestion, while ClickHouse powers columnar analytics and PostgreSQL stores application state. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

OpenSearch is a search and analytics platforms, powering full-text search, log analytics, observability, and AI-powered vector retrieval at petabyte scale. The distributed engine provides BM25 full-text search alongside k-NN vector search using NMSLIB, Faiss, and Lucene libraries, enabling semantic search, hybrid search combining keyword and vector scoring through normalization processors, neural sparse search, and retrieval-augmented generation workflows with built-in ML Commons for model hosting. OpenSearch Dashboards delivers interactive visualization with Discover for log exploration, custom dashboards, alerting, anomaly detection using Random Cut Forest algorithms, and Security Analytics with detection rules mapped to MITRE ATT&CK. Native Prometheus integration with full PromQL support unifies metrics alongside logs and traces in a single observability interface, while Data Prepper handles telemetry ingestion from OpenTelemetry collectors, Fluent Bit, and Logstash-compatible pipelines. SQL and Piped Processing Language queries with a visual PPL builder enable analysts to query data without learning the native DSL. Index State Management automates index lifecycle with rollover, shrink, and delete policies, while cross-cluster replication and searchable snapshots on S3-compatible storage provide disaster recovery. Scoped API keys, field-level security, document-level security, and audit logging deliver enterprise-grade access control. Docker Compose deploys multi-node clusters alongside the Kubernetes operator for orchestrated production environments. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

HyperDX correlates logs, metrics, traces, session replays, and errors in a single interface so engineers can resolve production incidents in minutes instead of hours. Nearly 10,000 GitHub stars reflect its role as the integrated UI layer for the ClickStack blueprint endorsed by ClickHouse. The platform connects to any ClickHouse cluster as its storage backend, working with existing table structures without requiring data migration or proprietary ingestion formats. An intuitive Lucene-like search syntax supports full-text queries and property filtering like level:err or service.name:api without needing SQL, while native JSON string querying and event delta analysis surface anomalies in high-cardinality datasets. One-click cross-signal correlation lets you jump from a log line to its distributed trace, from a slow span to associated logs, or from a frontend session replay to the backend errors it triggered. The OpenTelemetry Collector accepts telemetry via OTLP on gRPC port 4317 and HTTP port 4318, supporting automatic instrumentation for Node.js, Python, Java, Go, Ruby, and browser applications. APM tracks HTTP request latency, database query duration, and external service calls with trace waterfall visualizations. Configurable alerts trigger via webhook, Slack, PagerDuty, or email when thresholds are breached. Deploys via Docker Compose with ClickHouse, MongoDB, Redis, and the OpenTelemetry Collector. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Page views, referrers, browsers, and screen sizes - Ackee delivers the analytics developers actually check, from a deliberately minimal Node.js and MongoDB stack that skips both Matomo's weight and Google Analytics' cloud dependency. Its defining constraint is anonymization: no cookies, no unique user tracking, and a multi-step anonymization process that keeps visitors unidentifiable while the aggregate numbers stay useful. In its default anonymous mode Ackee collects no personally identifiable information at all, which means GDPR and CCPA compliance out of the box and no cookie consent banner on your sites. A detailed mode adds screen size, language, and per-visit referrers - still without cookies or fingerprinting. Integration mirrors the Google Analytics pattern: create a domain in settings, drop the generated ackee-tracker snippet into your pages, and data appears in a clean single-page dashboard. One instance tracks multiple domains, and custom events capture button clicks, signups, and conversions. The distinctive engineering choice is the fully documented GraphQL API: everything the dashboard shows comes from that API, so you can query active visitors, average duration, and view statistics programmatically, feed data in from apps and services beyond websites, or build an entirely custom interface on top. If you want bare-minimum analytics with a real API and zero privacy anxiety, this is the tool.