Real-Time NYSE/NASDAQ Data Feed

@onkarkulkarni8

Hello, I your "Real-Time NYSE/NASDAQ Data Feed" project description in detail and undertood your requirements. I've worked on many PHP projects in recent times. So I am confident on achieving your expected Goals. Please initiate a communication thread to discuss further and start with the project. ⭐ 5.0/5 from a recent client: "Project was delivered before Time with Best professional Knowledge One could ever held. Thanks for the support" Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@vishal1145

Your platform will fail during the first market spike if you rely on REST polling instead of WebSocket streaming—REST introduces 200-500ms of unnecessary latency per request, and providers like Polygon throttle REST calls to 5 requests per second on standard tiers. That bottleneck will make your charts lag behind the market when volume surges. Quick questions - are you planning to support options chains or just equities for now? And what's your expected concurrent user count at launch so I can size the WebSocket connection pool correctly? Here is the architectural approach: - POLYGON/IEX WEBSOCKET: Establish persistent WebSocket connections with automatic reconnect logic and exponential backoff to handle provider outages without dropping your entire feed. - NODE.JS + REDIS PUB/SUB: Buffer incoming ticks in Redis and fan out to multiple client subscriptions so one slow consumer doesn't block the entire stream during high-frequency updates. - RATE-LIMIT MIDDLEWARE: Implement token-bucket throttling at the API gateway layer to prevent your app from breaching provider quotas and getting blacklisted mid-session. I've built similar real-time data pipelines for 2 fintech platforms that now handle 10K+ concurrent WebSocket connections with sub-100ms latency. Let's schedule a 20-minute technical call to align on provider selection and hosting architecture before you commit to a build.

@Prutheus

Ultra-low-latency and a clean subscribe API are two different problems, and the honest first question is which one you actually need — because true sub-millisecond market data is a direct-feed and colocation problem, while sub-second through a provider like Polygon is a straightforward, affordable build. Your description says sub-second, so I will scope to that. Plan: - Provider recommendation with actual numbers: Polygon, IEX and Alpha Vantage differ sharply on latency, coverage and cost per symbol. I will lay out the trade-off rather than just pick one. - Ingestion service holding one upstream connection and fanning out to your clients, so the number of app users never multiplies your provider cost or hits rate limits. - WebSocket for streaming quotes and ticks, REST for snapshots and fundamentals — charts need both, and building only one always leads to bolting on the other. - Reconnect with gap recovery, because the upstream will drop and a chart with a silent hole in it is worse than a visible error. - Documented API so the rest of your application can subscribe cleanly. Proof: real-time data ingestion and 24/7 pipelines in production, plus Node and Python backends serving live data to frontends. Question: how many concurrent users and how many symbols in the first release? That drives both architecture and provider cost more than anything else. Martin

@ASSAMWEB

Greetings, I have reviewed your project description and recently worked on a similar project. I believe I can help you deliver this successfully. Let’s open a chat to discuss your requirements in detail and determine the best approach for your project. Regards

@shayankhan333

Hi, I will wire live NYSE and NASDAQ quotes into Trade for Tomorrow with sub-second refresh and steady reconnects during peak hours. I'll stream level-1 quotes and trade ticks over WebSocket in Node, using Polygon unless you prefer another provider. You will receive: WebSocket feed for any NYSE or NASDAQ ticker Reconnect, throttling and error handling Sample script and README with setup I understand latency under 300 ms matters most, so I'll tune and stress-test before handover, ready in about 5-6 days. 1) Do you already have a Polygon or IEX account, or should I recommend one? Best regards, Shayan

@sarimshoaib1425

100% doable. Built real-time backend systems before, including an AI platform serving 200 live users, so wiring a resilient market data feed is solid ground. I'd connect to Polygon or IEX Cloud, stream quotes over WebSocket with reconnect and throttling built in, and expose it through a documented API your app can subscribe to instantly. Built in Node.js for easy scaling toward execution features later. Can have a live demo running within a few days. Feel free to DM me for case studies. Or check the projects on my profile. Let's do it.

@Jennycreation

With 17+ years of comprehensive experience in web, window, and Android development, I'm confident that my team and I are the best fit for your project. Our expertise lies in various technologies including JavaScript and Python - frameworks which can ably handle your real-time data feed requirements for "Trade for Tomorrow". In fact, we have successfully developed and deployed similar solutions for stock-trading platforms before. In addition to our development prowess, my experience as a Crypto Currency Expert and Stock Trading Software expert will allow me to bring a unique perspective to your project. Having developed stock trading software and utilized Python for scraping and automation work extensively, providing the efficient NYSE/NASDAQ data feed you need will be well within our comfort zone. Moreover, my knowledge of ASP.NET C#, making use of SQL Server databases, and developing with a full responsive Bootstrap framework can also prove invaluable in scaling your platform down the road. Rest assured, our customer satisfaction guarantee is not just a platitude. We know that substantial planning goes into a project like yours, thus we commit to working 24x7 until the delivery surpasses your expectations. Appreciating the time-sensitivity of this project, my team can produce a demo at the earliest with Polygon - a proven real-time data provider we highly recommend. Give us a chance to prove our worth!

@prashanpatel557

Hello, I can build the real-time NYSE/NASDAQ market-data layer for Trade for Tomorrow with a focus on low latency, reliability, and scalability. I have experience with Python trading systems, real-time market data, WebSocket integrations, REST APIs, broker/exchange APIs, logging, reconnection handling, and trading-platform backends. My approach would include: - Integrate a suitable real-time provider such as Polygon or another provider based on your required NYSE/NASDAQ coverage and subscription. - Stream Level-1 bid/ask quotes, trade ticks, and available fundamental data. - Expose the feed through a clean WebSocket/REST service for your frontend and future trading modules. - Implement async processing, throttling, reconnect/retry logic, heartbeat monitoring, and structured error logging. - Build a lightweight Python test dashboard/script showing live quotes and latency. - Design the service so additional symbols, users, charting, and future trade execution can be added without rebuilding the core. - Provide complete setup documentation covering API keys, endpoints, rate limits, deployment, and monitoring. I would benchmark the feed during live market hours and identify any provider-side latency or rate-limit constraints before finalising the architecture. Estimated delivery: 5–8 days for the initial production-ready data layer and demonstration. I can start with the provider/API evaluation and a working live-feed prototype.

@tyronet2

Quick calibration first — "ultra-low-latency" on Polygon/IEX/Alpha Vantage is a contradiction. True ULL means co-located FPGA gear straight to exchange gateways, $10k+/mo floor. What you actually want (sub-300ms) is retail-tier WebSocket feeds handled well: no unnecessary hops, no serialization bloat, no reconnect gaps. Very doable. Stack fit: Python 9 years (FastAPI, async) + Node.js, real-time WebSocket + Kafka/RabbitMQ pipelines from Marin Software (event-driven pricing at scale), plus broker/API integration work with rate limiting, reconnect + exponential backoff, heartbeat monitoring. Recommended stack: Polygon as provider (best coverage, reliable WebSocket, IEX Cloud is retiring), Python + FastAPI + websockets library for ingest, Redis Streams as buffer so downstream consumers subscribe without pressuring the exchange connection, a WebSocket endpoint fanning out to your app, REST endpoints for last-tick and fundamentals lookups. Deploy to a VPS near Polygon's US-East region (sub-100ms round-trip from any US-East cloud). Milestone deliverable: level-1 quotes + trade ticks + basic fundamentals (P/E, market cap) via Polygon reference endpoints, throttling per your plan tier, auto-reconnect with backoff + duplicate detection, plus a Python sample script + minimal HTML dashboard proving live streaming.

@alluankit01

Hi, I can build the real-time NYSE/NASDAQ market data layer for Trade for Tomorrow with a clean REST/WebSocket API, reconnect logic, throttling, and a working demo dashboard/script. I will first confirm your preferred provider, budget for market-data subscription, tickers, hosting setup, and latency target. My recommendation is to use Polygon or IEX depending on required data depth, pricing, and reliability. Then I’ll implement a scalable data service that streams level-1 quotes, trade ticks, and basic fundamentals to your platform. I’m comfortable with Python, Node.js, WebSocket APIs, REST APIs, financial data providers, real-time streaming, reconnect handling, rate-limit management, error logging, API documentation, and lightweight dashboards. Deliverables will include: * Real-time data provider integration * NYSE/NASDAQ quote streaming * Trade tick data support * Basic fundamentals endpoint * REST or WebSocket API * Reconnect and retry logic * Throttling/rate-limit handling * Error logging * Sample dashboard or script * 30-minute stress-test support * README with setup and endpoints I’ll focus on a reliable, well-documented live data layer that updates bid/ask prices in real time and can scale later for portfolio tracking and trade execution. Best regards Ankit

@MuhammadAsad108

✔ I deliver 100% work — 99.9% is not for me. ✔ Workflow Diagram Market Data Provider ⟶⟶ WebSocket/REST Integration ⟶⟶ Quote & Trade Processing ⟶⟶ Resilient API Layer ⟶⟶ Stress Testing ⟶⟶ Documentation & Deployment Key Highlights ✔ Real-time NYSE & NASDAQ integration using Polygon, IEX, or another suitable provider based on latency, coverage, and API limits. ✔ Level-1 market data — live bid/ask quotes, trade ticks, and basic fundamental data. ✔ Low-latency WebSocket/REST API designed for sub-second updates and future trading-platform expansion. ✔ Reliable connection handling — throttling, reconnect logic, retries, validation, and graceful error handling. ✔ Production-ready architecture using Node.js/Python with clean, documented APIs. ✔ Live test dashboard or Python/Node.js sample demonstrating real-time ticker updates. ✔ Stress testing during market hours with latency and connection monitoring. ✔ Complete README covering setup, API keys, endpoints, rate limits, deployment, and maintenance. ✔ Scalable foundation so portfolio tracking and trade execution can be added later. Best Regards, Asad Full-Stack Developer | API Integration | Financial Systems

@mikes126

Hi there , let's have short meeting if you wanna discuss your stock data feed build. I will connect your platform to Polygon or IEX Cloud for real time NYSE and NASDAQ quotes. The feed will stream level one data through a clean WebSocket API with sub second latency. I will add throttling reconnect logic and error handling to keep the service stable always. You will get a lightweight Python dashboard proving the feed is live and publishing accurately. The README will cover setup keys rate limits and all endpoints for easy integration. I have built similar financial data feeds before and can share demos in our chat.

@Sahyadri96

Completed projects till now 1) Python + DhanAPI +Excel + VBA option scalping strategy 2) Python 21 EMA and 9 EMA crossover strategy on DhanAPI 3) Google sheet + FyersAPI trading 4) Google sheet + Algomojo + Upstox 5) Tradetron Banknifty option scalping strategy 6) Excel 2600 NSE 10 years data 7) Copytrading using python 8) Tradetron Supertrend + MACD Crossover Strategy 9) Dhan option chain with Greeks in Google spreadsheet via Google Appscript 10) Backtesting of Nifty options for wait and trade strategy 11) Trigger orders for Dhan Nifty options 12) Shoonya API:- Wait and trade strategy 13) Tradetron: RSI + ADX + EMA strategy 14) Python Moving avarage channel trading Algo 15) Kotak Neo: Turtle scalping strategy for options 16) Fyers Filtered option chain in Excel 17) Binance Bitcoin tradingview strategy python bot 18) Fyers Tradingview python bot 19) Dhan Python order manager I can deliver any project in Trading. Readymade setups for Python available

@UmairBuildsAI

Keeping latency consistently under 300ms during peak market hours is where most real-time feeds struggle, so reconnect logic and throttling need to be built in from day one, not bolted on after something breaks under load. I've built reliable, real-time data pipelines before, including LOADEX, which handled live status tracking and automation at scale, and the Lead Enrichment Pipeline, built with resilient data flow and error handling across multiple sources. Portfolio: https://www.freelancer.pk/u/UmairBuildsAI I'd recommend Polygon for reliable NYSE and NASDAQ coverage, building the feed with Node.js and WebSockets for sub-second updates, with solid reconnect and throttling logic baked in, then expose it through a documented API and hand off a lightweight dashboard proving the feed is live, along with a clear README covering setup and rate limits. Let's connect on a call and discuss. Best Regards, Umair

@rakhshanz3

As an experienced AI and software development professional with nearly 20 years in the industry, I'm confident that I am the perfect fit for your real-time data feed project. My academic background in Computer Science and PhD in Artificial Intelligence combined with my hands-on work on large-scale applications for multinational companies equip me well to take on the challenges of designing and developing a reliable, ultra-low-latency real-time data feed. Throughout my career, I've built numerous AI-driven solutions and developed full stack SaaS applications with scalable front-end and back-end architecture - skills that are highly applicable to your project needs. Additionally, I have comprehensive knowledge in API development, cloud deployment, database design, and system optimization - all aspects critical to executing your project successfully. My proficiency in Node.js will ensure effective use of various datasets for direct consumption by your application. Furthermore, I've had extensive experience integrating third-party APIs, something that would be pertinent in this project where you require connection to real-time providers like Polygon, IEX Cloud or Alpha Vantage.

@NobleSourcing

I am excited about the opportunity to help build your stock-trading platform, “Trade for Tomorrow.” With my recent experience implementing real-time data feeds for similar projects, I am confident in my ability to connect to a reliable provider and deliver a robust API. I understand the importance of ultra-low latency and have successfully managed high-volume data streams with minimal latency in the past. I am ready to provide a lightweight dashboard, ensure resilience during peak hours, and document everything clearly for easy setup. Thank you for considering my proposal. Tegan

@Gurpreetsing343

As the CEO of GSINFOTECHH OPC Pvt. Ltd., I fully understand the crucial nature of real-time data in your stock-trading platform, and I'm confident my team has the expertise to deliver. We are highly skilled in JavaScript, Node.js, and Python which are essential for consuming and streaming real-time data via RESTful or WebSocket APIs. This will ensure we offer you a clean & well-documented API while guaranteeing sub-second refresh rates. Additionally, our experience in not just rooting out the best data providers such as Polygon, IEX Cloud, or Alpha Vantage, but integrating their services into platforms as complex as yours is unmatched. We have built tools that scrape financial data needed for quantitative analysis as well doInBackground API calls to Parse JSON responses and updates to CSV,json,XLS files for efficient trading algorithm analysis. For your specific project, we'll also include simple throttling, reconnect logic, and error handling to maximize the resilience of your system during high-volume sessions. Our proficiency extends beyond mere software development. At GSINFOTECHH, we focus on aiding businesses with their digital transformation journey. Your project falls perfectly within our scope; we've previously designed financial systems, created custom tools for algorithmic trading with real-time interaction plus dashboard or script based views for easier understanding.

@muhammadaariyan

Hi, I have 2 plus years of experience building Node.js, Python and REST API integrations for real time data workflows. Market data gaps or unstable reconnects can make charts unreliable exactly when volatility is highest. I can build the feed layer around a provider such as Polygon, using WebSockets for live quotes and trades, REST for fundamentals, with reconnect handling, throttling and structured error recovery. WebSockets are preferable here because persistent connections avoid repeated polling overhead and provide lower latency for streaming market events. Would you prefer Polygon as the initial provider, or should I evaluate alternatives against your sub 300 ms target? Happy to discuss details in chat. Regards, Muhammad Arriyan

@anas389

Good day! I understand you need a reliable, low latency market data layer for Trade for Tomorrow supporting real time NYSE and NASDAQ quotes, trade ticks, and fundamentals. I can integrate a suitable provider such as Polygon or IEX, build a resilient WebSocket or REST service with reconnect logic, throttling, error handling, and a clean API for your trading platform. A few questions: 1. Do you already have a preferred market data provider? 2. Do you prefer Node.js, Python, or Go? 3. Where will the service be hosted? I have experience with real time APIs, WebSockets, Node.js, backend architecture, and performance optimization. I would be happy to build the data layer and provide a working demo with documentation. Thank you!