Key Challenges & Solutions
Explosive Growth of Market & Transaction Time-Series
Every trading venue, brokerage, and financial institution produces continuously expanding datasets, often terabytes per day. Retaining years of historical data becomes expensive, slow, and operationally complex.
How Byte2Bit solves it:
- Atlas compresses financial time-series with industry-leading ratios, often achieving 3×–7× reductions.
- Significant decrease in data footprint enables long-term retention of high-resolution tick data and backtesting datasets.
- Lower storage cost directly improves margins for data-heavy financial workflows.
Heavy Query Loads & Slow Analytics on Large Datasets
Financial analysts and machine-learning systems must scan billions of datapoints for patterns, anomalies, or opportunity signals. Traditional compression slows access, hurting responsiveness of quant pipelines and research tools.
How Byte2Bit solves it:
- Atlas provides fast compression and near-instant decompression, enabling low-latency access to archived datasets.
- Downstream analytics from quant models to compliance checks run faster on compressed data.
- Ideal for high-frequency trading research, risk simulations, and large-scale backtesting.
Underperformance of Generic Compression Algorithms
General-purpose compressors like Zstd or LZ-based systems are not optimized for financial tick patterns, multidimensional order-book data, or sparse-but-bursty event streams. This leads to wasted compute and sub-par compression ratios.
How Byte2Bit solves it:
- Atlas is tailored for structured, high-variance time-series typical in finance.
- Consistently outperforms Zstd, XZ, and similar algorithms across real-world financial workloads.
- Delivers better ratio, lower latency, and greater computational efficiency for trading firms, banks, and fintech platforms.
Use Cases
High-Frequency Trading
Enable low-latency access to market data for trading research.
- Fast compression/decompression
- Real-time analytics
- Risk simulation support
Backtesting & Research
Support large-scale backtesting with efficient data storage.
- Long-term data retention
- High-resolution tick data
- Quant model acceleration
Compliance & Analytics
Accelerate compliance checks and analytics pipelines.
- Fast query performance
- Historical data access
- Cost-effective storage
Benefits
Compression Ratio
3X–7X
Financial Time-series
Performance
5X
Better Than Zstd
Storage Cost
50%+
Reduction
Query Speed
Near-instant
Decompression