OpenBB stands as the world's most popular open-source finance repository — an Open Data Platform that evolved from a pandemic-era Reddit post into a full-blown infrastructure layer challenging Bloomberg's $25 billion empire. The "connect once, consume everywhere" architecture consolidates proprietary, licensed, and public financial data sources into multiple consumption surfaces simultaneously: Python environments for quants building models, OpenBB Workspace and Excel for analysts creating dashboards, MCP servers for AI agents performing automated research, and REST APIs for custom applications. The modular extension system supports dozens of data providers including Yahoo Finance, Alpha Vantage, FRED, Intrinio, Polygon, and Tradier with standardized schemas that normalize responses across vendors. The CLI offers a terminal-style interactive interface with autocomplete, parameter hints, and chart rendering for rapid data exploration. Provider routing handles authentication, rate limiting, and response normalization transparently so switching between free and premium data sources requires changing a single parameter. The platform covers equities, options, fixed income, crypto, forex, ETFs, mutual funds, economics, technical analysis, quantitative analysis, and alternative data across global markets. AI agent integration exposes every data endpoint as tool-callable functions with schema discovery enabling LLMs to query financial data programmatically. Install via pip with Python 3.9+ and deploy the REST API server for team access. 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.

OpenStock delivers a production-ready financial market terminal that unifies real-time equity pricing, technical analysis, and multi-asset watchlists into a personal self-hosted dashboard. Investors can monitor equities across thirty international exchanges, inspect live candlestick charts powered by TradingView, and evaluate technical momentum oscillators without paying recurring platform subscriptions. The global command palette accessible via keyboard shortcuts enables instantaneous ticker discovery across global exchange symbols and economic sectors. Users can organize individual stock watchlists in MongoDB, configure automated price threshold alerts triggered every fifteen seconds, and review cross-platform sentiment scores synthesized from Reddit, X, and financial news feeds. The built-in automation engine schedules weekly digest reports and event-driven notifications dispatched directly to your inbox through Nodemailer transports. Responsive market heatmaps and top-mover widgets surface daily sector performance before the opening bell rings. Deployable via Docker Compose with dedicated MongoDB persistence, the platform scales across multi-key Finnhub rate limits effortlessly. 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.

Powering trading floors at firms processing millions of market data events per second and trusted by organizations including Airbus, Yahoo, and Copenhagen Atomics, QuestDB has earned over 17,000 GitHub stars as the time-series database that refuses to make you choose between ingestion speed and query latency. The column-oriented, time-partitioned storage engine processes millions of rows per second on ingest through write-ahead logging with instant durability, while SIMD-accelerated parallel execution returns analytical queries over billions of rows in milliseconds. Time-series SQL extensions add ASOF JOIN for point-in-time lookups across tables with misaligned timestamps, SAMPLE BY for downsampling at arbitrary time intervals, LATEST ON for last-value queries, and WINDOW JOIN for sliding window aggregations — all through standard SQL syntax accessible via the PostgreSQL wire protocol, REST API, or the QuestDB Wire Protocol (QWP) that streams Apache Arrow at 220 million rows per second. Multi-tier storage automatically moves data from the WAL through native columnar format to Parquet files on S3-compatible object storage, keeping hot data fast and cold data portable without manual tiering. The built-in web console provides an interactive SQL editor with syntax highlighting, autocomplete, and charting for quick data exploration. Views, materialized views, and n-dimensional arrays support real-time analytics, while native Parquet export enables direct integration with Python, DuckDB, and AI/ML frameworks. 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.

Screen equities against dozens of technical indicators, backtest algorithmic trading strategies, and spot intraday market anomalies using Tick Stock Panel, a self-hosted quantitative analysis workbench. Traders can filter entire exchanges across technical indicators including moving averages, relative strength index, and Bollinger bands with near-instantaneous execution. The platform provides a full backtesting environment where users test customized entry and exit rules, account for simulated slippage and commission fees, and review streamed performance metrics. Dedicated monitoring modules track intraday volume spikes, price breakouts, and multi-day limit streaks with automated alert dispatching to messaging channels and voice announcements. Users can explore individual stock profiles featuring multi-dimensional technical breakdowns, financial balance sheets, and automated event post-mortems generated via integrated language models. Visual factor mining tools allow analysts to discover uncorrelated signals and assemble composite portfolio screens without external database overhead. An interactive dashboard aggregates sector rotations, hot concept heatmaps, and customizable watchlists into modular operational views. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

PanWatch's three scheduled AI agents plan the trading day before the bell, watch the session, and review it after the close for your China A-share, Hong Kong, and U.S. holdings. Day one begins with the portfolio: several brokerage accounts, holdings and profit and loss, and search for stocks or listed ETFs by code or name. The pre-market agent folds overnight moves, news, and technical structure into that plan and skips exchange holidays. Through the session, the intraday monitor watches for unusual moves and technical signals. Price alerts combine price, percentage change, turnover, and volume ratio with AND/OR logic, cooldowns, and expiry times. Each rule picks its own channel from Telegram, WeCom, DingTalk, Feishu, Bark, or a webhook. Spot something odd? The brain icon next to a holding starts TradingAgents, where four analyst roles feed a bull and bear debate, a risk review, and a portfolio-manager decision, with the reasoning trail in the app and your notifications. The opportunities screen ranks AI-scored ideas with entry levels and targets, and paper trading simulates signal-based entries and exits and tracks equity and performance. At day's end, the daily report reviews the session and prepares the next trading day's plan. OpenAI-compatible providers or local Ollama models power the analysis, and the PWA installs on a phone in English or Simplified Chinese. 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 atop the TauricResearch TradingAgents framework with nearly 100,000 GitHub stars, TradingAgents GUI transforms a CLI-only multi-agent LLM stock analysis pipeline into a polished web application accessible at localhost:5000. The system deploys twelve specialized AI agents — fundamental analysts, sentiment experts, technical analysts, bull and bear researchers, a trader, risk management team, and portfolio manager — who collaboratively debate market conditions through structured LangGraph workflows before producing a final BUY, SELL, or HOLD recommendation. The interface supports ten LLM providers including OpenAI, Anthropic, Google, OpenRouter, DeepSeek, Ollama, xAI, Qwen, GLM, and MiniMax, with a first-run wizard that auto-detects configured API keys and tests connections. A live pipeline visualization shows each agent's status with real-time progress bars, while the tabbed output area separates Live Feed, Reports preview, and Tool calls into dedicated panes. The three-pane Reports tab provides searchable indexing, table-of-contents navigation, and export to Markdown, HTML, or PDF formats. Report length control across Concise, Standard, and Comprehensive modes saves up to 50% on token costs. Multi-session chat allows pinning past reports as grounding context with live token counting and context-window warnings. Three built-in themes — Terminal, Modern, and Bloomberg — persist per browser. Docker Compose deployment maps port 5000 with persistent report storage. 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.

Trading alerts from TradingView, Amibroker, ChartInk, Excel, or a Python script turn into orders at your own broker through OpenAlgo, a self-hosted trading desk for Indian markets. One REST API handles orders, positions, holdings, funds, quotes, and market depth across more than 35 brokers, including Zerodha, Upstox, Angel One, Fyers, and Dhan, while a WebSocket feed streams live prices. Strategies can be wired together without code in Flow, a drag-and-drop canvas of data, indicator, condition, and order nodes with webhook triggers, or written in Python and scheduled with start and stop times in the built-in editor, each in an isolated process with live logs. The charting terminal places orders straight from the chart, with layouts of up to eight charts, over 100 indicators, drawing tools, and bar replay. Options traders get an option chain with live Greeks, OI tracker, max pain, straddle charts, a 3D volatility surface, a GEX dashboard, and a strategy builder with payoff diagrams. Analyzer mode runs any strategy against real market data with 1 crore rupees of sandbox capital. Semi-auto mode in the Action Center holds each order for your approval, and the AI agent charts, analyzes, and drafts strategies but pauses for sign-off on every order. Telegram alerts, a latency monitor, a P&L tracker, and Historify downloads with CSV and Parquet export cover daily operations. 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.

A trading journal you host yourself, Trade Journal rebuilds broker fills and statement exports into round-trip trades, a profit and loss calendar, and daily notes that show what actually works. Read-only sync covers more than twenty brokers and exchanges, including Alpaca, Binance, Coinbase, Kraken, and IBKR Flex. Statement import auto-detects TradingView, MetaTrader, NinjaTrader, Tradovate, and thinkorswim files, handles TradeZella and Tradervue CSV migrations, and maps columns for anything else. Trades can be matched first-in-first-out, last-in-first-out, or by weighted average, with partial fills, scale-ins, and futures multipliers handled. The dashboard offers gauges, cumulative and daily P&L, an Edge Score radar, and cards you can rearrange into named layouts, while Reports break results down by symbol, tag, mistake, playbook, weekday, and time of day. Each trade page charts entries and exits and can replay candles you load, with estimated MAE and MFE. Daily journal pages hold Markdown notes, templates, attachments, and voice dictation, and optional AI recaps use your own Anthropic or OpenAI key or a local Ollama model. Playbook checklists score rule adherence, a prop firm ledger tracks costs and payouts, and privacy mode masks every amount. 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 1,450+ GitHub stars and a live demo on Vercel, this Bloomberg Terminal clone delivers a professional-grade financial dashboard without the $24,000 annual seat license. The Next.js 15 App Router with React 19 and TypeScript serves a single-page terminal interface optimized for constantly mutating financial data, with partial pre-rendering enabling sub-500ms initial loads even on data-heavy views. Upstash Redis caches AlphaVantage market data to minimize API calls while maintaining sub-second update latency through React Query polling with configurable refresh rates. OpenAI integration provides AI-powered market insights, sentiment analysis, and trend interpretation directly within the terminal interface. Multiple specialized views cover market data tables with bid/ask spreads, financial news aggregation with category filtering, market movers highlighting top gainers and losers, and volatility analysis with historical comparison charts. Jotai atoms manage local state for watchlists, layout preferences, and terminal sessions while React Query handles server-state synchronization with aggressive stale-while-revalidate caching. The shadcn/ui component library with Tailwind CSS delivers accessible, keyboard-navigable interface elements styled after Bloomberg's iconic dark terminal aesthetic. Security features include origin restriction, rate limiting via Redis, and Zod-based input validation on all API routes. Motion (formerly Framer Motion) animates transitions between views and data updates without layout shift. 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.

When dashboards must answer in under a second over billions of streaming events, Apache Druid is the real-time analytics database built for the job. Point a supervisor at an Apache Kafka topic or Amazon Kinesis stream and events are queryable on arrival, late data included, with exactly-once guarantees. Batch loads run as SQL: INSERT and REPLACE statements ingest files, and EXTERN reads external sources. Schema auto-discovery adds new columns and types as data lands. Joins run at ingestion or at query time. A web console gathers the daily work in one place: a tabbed Query view with EXPLAIN PLAN and query history, a Connect external data wizard, and pages for datasources, segments, retention rules, supervisors, tasks, services, and lookups. Configurable tiers place hot and cold data on different hardware. Quality-of-service settings shield priority workloads from heavy ones. Clickstream analytics, ad campaign reporting, network telemetry, application performance tracking, and IoT metrics all fit. Applications connect over the HTTP SQL API or the Avatica JDBC driver, and native JSON queries remain available for advanced needs. 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.

Exploratory data work, teaching material, and research code all live in the same browser tab with JupyterLab, the web workspace of Project Jupyter. Notebooks combine runnable code cells, Markdown, and rich output such as images, JSON, and Vega charts, and they use the same notebook format as the classic Jupyter Notebook. Any Jupyter kernel can execute the code, so Python, R, and other languages share one interface, and code inside plain text files such as Markdown or LaTeX can be run interactively as well. Tabs and splitters arrange documents side by side, and a notebook's cell outputs can be mirrored into their own tab to build a simple dashboard with interactive controls. Code consoles serve as scratchpads linked to a notebook kernel, while full terminals run system shells such as bash on the server. A visual debugger offers breakpoints, a call stack, and a variable explorer for kernels that support the Jupyter debug protocol. Markdown, CSV, and Vega documents show a live preview as they are edited, and built-in viewers handle images, JSON, and PDF files. The Extension Manager installs themes, editors, and renderers from PyPI, and real-time collaboration becomes available by adding the jupyter-collaboration extension. Access is protected by a generated token unless a password is set. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-3-Clause licensed.