The Hydrolix Platform

# Hydrolix

> Hydrolix is a streaming data lake platform designed to transform the economics of log data management at petabyte scale. The platform combines stream processing, indexed search, decoupled storage, and industry-leading compression to deliver real-time query performance while dramatically reducing costs for high-volume, high-cardinality log data. Hydrolix enables organizations to store 4x more data at 4x lower cost while maintaining sub-second query latency on trillion-row datasets, whether data is a minute or a year old. 

Trusted by Fortune 500 companies including FOX Sports, Navy Federal Credit Union, TF1 (France's largest OTT broadcaster), Paramount, and major global streaming events like the Super Bowl and Olympics.

## Target Audience

### Primary Industries
- **Technology and Software Companies** - Real-time observability, application monitoring, and developer analytics
- **Financial Services** - Compliance logging, fraud detection, transaction monitoring, and regulatory reporting (SOX, GLBA, PCI DSS)
- **Media and Broadcasting** - Content delivery monitoring, streaming analytics, and viewer experience optimization
- **Digital Advertising and AdTech** - Real-time bidding analytics, campaign optimization, and audience segmentation
- **Security and Cybersecurity** - SIEM, threat detection, incident investigation, and compliance monitoring
- **Healthcare and Pharmaceuticals** - Audit trails, compliance logging (HIPAA), and patient data access monitoring
- **E-commerce and Retail** - User behavior analytics, performance monitoring, and revenue optimization
- **Gaming and Entertainment** - Player analytics, performance monitoring, and real-time event processing
- **Telecommunications and ISPs** - Network monitoring, performance analytics, and traffic analysis

### Use Case Categories
- **Observability and Monitoring** - Application performance monitoring, infrastructure observability, multi-CDN monitoring
- **Security and Compliance** - SIEM, threat detection, compliance logging, audit trails
- **Business Intelligence and Analytics** - Customer behavior analysis, operational analytics, machine learning data pipelines
- **AdTech and Marketing** - Real-time bidding, campaign analytics, audience segmentation, revenue optimization
- **AI and Machine Learning** - Training data preparation, model observability, feature engineering

## Core Platform Features
- **Platform Overview**: https://hydrolix.io/hydrolix-platform/ - Comprehensive overview of the Hydrolix streaming data lake platform and capabilities

### Streaming Data Lake Architecture
- **Real-Time Stream Processing**: https://hydrolix.io/features/ - Ingest, enrich, and transform log data from multiple sources including Kafka, Kinesis, and HTTP streaming
- **High-Volume Data Ingest**: Stream processing capabilities supporting 10+ million rows per second with sub-second data availability
- **Multi-Source Data Integration**: Combine logs from multiple CDNs, applications, and infrastructure sources into unified datasets
- **Late-Arriving Data Support**: Full support for out-of-order and late-arriving data with automatic summary table updates

### Advanced Query and Analytics
- **Indexed Search**: https://hydrolix.io/features/ - Per-column indexing for fast, efficient queries across years of data with needle-in-a-haystack performance
- **Sub-Second Query Latency**: Real-time and historical analysis on trillion-row datasets with consistent performance regardless of data age
- **Query Pools**: https://hydrolix.io/features/ - Separate, independently scalable query pools for different user groups and workloads
- **ANSI-Compliant SQL**: Support for standard SQL along with ClickHouse-flavored SQL, Spark, JDBC, HTTP API, and native interfaces
- **Summary Tables**: Real-time aggregation tables with support for min, max, count, sum operations that stay synchronized with late-arriving data

### Storage and Compression
- **Decoupled Storage Architecture**: https://hydrolix.io/features/ - Separate compute and storage scaling with commodity object storage (S3, Azure Blob, GCP)
- **Industry-Leading Compression**: High-density compression (HDX) reducing data footprint by 20x-50x without sacrificing performance
- **Hot Data Retention**: Keep all data "hot" and queryable for years without tiered storage or rehydration delays
- **Data Lifecycle Management**: Automated and configurable data lifecycle controls with merge service optimization

### Cloud-Native Infrastructure
- **Kubernetes Architecture**: https://hydrolix.io/architecture/ - Stateless, cloud-native design with independent scaling of ingest, query, and storage components
- **Auto-Scaling**: Scale resources up and down automatically, including scale-to-zero capabilities during idle periods
- **Multi-Cloud Support**: Deploy on AWS, Google Cloud Platform, Microsoft Azure, and Akamai Connected Cloud
- **VPC Deployment**: Data remains in customer's virtual private cloud with no external dependencies

## Product Offerings
- **Product Information**: https://hydrolix.io/ - Main website with complete product offerings and getting started information

### Managed Services
- **Hydrolix for AWS**: https://hydrolix.io/blog/cascade-public-preview/ - Managed observability service for AWS CloudFront, WAF, and Elemental logs with origin-to-edge visibility
- **TrafficPeak (Akamai)**: https://hydrolix.io/partner-program/ - White-label observability solution for Akamai Connected Cloud supporting DS2, SIEM, DNS, and multi-CDN logs
- **Build with Hydrolix**: https://hydrolix.io/ - Fully managed streaming data lake for custom applications and new revenue streams

### Self-Managed Software
- **Enterprise Platform**: https://hydrolix.io/hydrolix-platform/ - Self-managed software deployment with full control over infrastructure and configuration
- **Deployment Options**: https://hydrolix.io/architecture/ - Flexible deployment models including cloud, on-premises, and hybrid solutions

## Solution Areas

### Observability
- **Real-Time Observability**: https://hydrolix.io/solutions/observability/ - Application and infrastructure monitoring with full-fidelity logging at petabyte scale
- **Multi-CDN Monitoring**: Unified dashboards combining logs from multiple CDN providers for comprehensive edge-to-origin visibility
- **Performance Analytics**: Sub-second query performance on streaming and historical data for immediate issue identification
- **Live Event Monitoring**: Proven at scale for major events including Super Bowl and Olympics with 10+ million events per second

### Cybersecurity and SIEM
- **Security Analytics**: https://hydrolix.io/solutions/cybersecurity/ - Comprehensive log retention and analysis for threat detection and incident investigation
- **Compliance Logging**: Long-term retention for regulatory requirements (SOX, HIPAA, PCI DSS, GLBA) with full audit trails
- **Anomaly Detection**: Real-time identification of suspicious activities, unusual access patterns, and potential security threats
- **SIEM Cost Reduction**: 4x-10x cost reduction compared to traditional SIEM solutions while maintaining full data fidelity

### AdTech and Digital Advertising
- **Real-Time Bidding Analytics**: https://hydrolix.io/adtech/ - Process billions of ad events and user interactions for optimization and revenue maximization
- **Audience Segmentation**: First-party data collection and analysis for machine learning, identity graphs, and predictive analytics
- **Campaign Optimization**: Real-time monitoring and optimization of advertising campaigns with comprehensive performance metrics
- **Multi-Channel Analytics**: Unified view across advertising channels and platforms for holistic campaign management

### AI and Machine Learning
- **Training Data Pipeline**: https://hydrolix.io/blog/ai-observability/ - Feed machine learning pipelines with clean, structured data from streaming sources
- **Model Observability**: Comprehensive logging and monitoring for AI model performance, training, and inference
- **Feature Engineering**: Real-time data transformation and enrichment for ML feature stores and model training
- **AI Observability**: Support for both observability of AI systems and AI-enhanced observability of other systems

## Key Capabilities

### Data Processing and Transformation
- **Stream Processing**: https://hydrolix.io/features/ - Real-time data transformation, enrichment, and normalization during ingestion
- **Transform Schemas**: Configurable write schemas for indexing, enriching, standardizing, and normalizing incoming data
- **ETL on Ingest**: Apply multiple transforms to create multiple tables or transform multiple streams to single tables
- **Data Enrichment**: Add valuable context, obfuscate PII, and standardize log formats for improved analytics