Understanding the Tech Stack Behind Angel One’s – Tick By Tick – Tradingview Charts

Charting accuracy defines a trader’s ability to analyze market movements effectively. Angel One’s charting solution processes historical and real-time price data with tick-by-tick precision, delivering insights through TradingView-style visualizations. The backbone of this system is a well-architected data pipeline that captures, processes, and stores tick data for real-time and historical analysis.

This article dives into how Angel One structures its market data processing, the importance of tick-by-tick charts, and the technology that makes it all possible.

What is Tick-by-Tick Data and Why Does It Matter?

Understanding Tick-by-Tick Charts

A tick-by-tick chart captures every trade in the market, in contrast to time-based candlestick charts that aggregate data over fixed intervals (1-minute, 5-minute, hourly). Tick charts provide a raw, uninterrupted view of market activity, including:

• Trade price
• Trade volume
• Timestamp

Since every price change matters in volatile markets, tick-by-tick data enables traders to analyze short-term price action with greater clarity.

Why Tick-by-Tick Data is Essential for Traders

1. Unfiltered Market Activity: Traders see every price change, allowing for better short-term trade execution.
2. High-Frequency Trading (HFT) Optimization: Algorithmic trading strategies depend on tick-level data to react instantly to market movements.
3. More Reliable Backtesting: Historical tick data allows traders to test strategies under precise market conditions.
4. Accurate Liquidity and Volatility Analysis: Understanding order flow helps in assessing market sentiment.

With the significance of tick data established, let’s explore how Angel One processes this information.

How Angel One Processes Historical Data for Charting

Angel One employs a hybrid on-premise and cloud-based architecture to ensure high-speed data processing and reliability. The pipeline consists of the following components:

1. On-Premise Data Collection

• Exchange Price Stream: Incoming trade data is captured from stock exchanges.
• Price Capture Engine: Aggregates and timestamps market data.
• Kafka for Streaming: Apache Kafka acts as a buffer, ensuring smooth data transfer with minimal latency.
• Kafka Mirror Maker: Replicates data from on-premise Kafka to AWS Managed Kafka for cloud processing.

2. AWS-Based Data Processing

• AWS Managed Kafka: Streams tick data to cloud-based consumers.
• Kafka Consumer: Processes data and aggregates different chart timeframes (1-minute, 5-minute, hourly, etc.).
• MySQL Database (AWS Aurora): Stores historical price data with optimized indexing for rapid retrieval.
• API Backend: Serves data for TradingView-like frontend applications.

3. Real-Time and Historical Chart Construction

• Live Charting: Tick data updates the last candle dynamically in real-time.
• Historical Charting: Precomputed candles are retrieved instantly upon request.
• Multi-Timeframe Generation: Higher timeframe candles (e.g., 30-minute, daily) are generated from 1-minute candles asynchronously.

This structure ensures chart updates remain accurate and fast, even during peak trading hours.

Challenges and Optimizations in Tick-by-Tick Processing

1. Managing High Data Throughput

• Optimization: Kafka is configured with acks=-1 and max.in.flight.requests.per.connection=1 to ensure message order integrity.
• Batching & Compression: Data is compressed and batched to optimize network efficiency.

2. Efficient Data Storage and Retrieval

• Optimization: Instead of using a time-series database like TimescaleDB, Angel One optimizes MySQL (AWS Aurora) with clustered indexes (scrip_code, timeframe, timestamp).
• Outcome: Query times are reduced to milliseconds, even under heavy load.

3. Handling High-Frequency Market Activity

• Optimization: Rather than calculating higher timeframe candles in real-time, the system precomputes them asynchronously, reducing real-time computation demands.

How Traders Benefit from Angel One’s Charting System

1. Instant Price Updates

Tick data ensures that price movements are reflected on charts within ~1 second latency.

2. Reliable Market Insights

Accurate historical tick data enables traders to refine their strategies based on real-world price action.

3. Scalable & High-Performance Infrastructure

The system can handle thousands of charting requests per second without compromising performance.

4. Enhanced Market Scanning

Chart-powered watchlists highlight stocks based on volume spikes, price breakouts, and trend reversals.

Angel One’s charting system is built for speed, accuracy, and scalability. By integrating tick-by-tick data processing with cloud infrastructure, the platform ensures traders get real-time and historical insights with minimal latency.

With AWS Hyderabad set to become a key disaster recovery hub, further enhancements will focus on reducing latency and increasing system resilience. As the demand for precise market data grows, Angel One’s infrastructure will continue evolving to meet the needs of modern traders.

Further Reading

For a deeper dive into Angel One’s charting infrastructure, check out the reference article by Abhin Hattikudru: 👉 Charting at Angel One