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DataFreeOpen Source
QUESTDB
High-performance time-series database for real-time analytics
Apache-2.0
ABOUT
AI systems that monitor models, log predictions, or track performance metrics need a storage backend that can ingest high-velocity time-series data and query it in real time. Traditional row-oriented databases struggle with the write throughput and query latency required for observability and monitoring at scale. QuestDB's columnar architecture and ingestion pipeline handle millions of rows per second while supporting standard SQL and PostgreSQL wire protocol, so teams can use their existing tools and skills.
INSTALL
brew install questdbINTEGRATION GUIDE
1. Store and query LLM inference latency and token usage metrics for production monitoring dashboards
2. Log prediction drift and model performance metrics over time for ML observability pipelines
3. Track feature store access patterns and embedding cache hit rates for AI system optimization
4. Time-series analytics on sensor data from IoT and edge AI deployments at high ingestion rates
5. Build real-time anomaly detection pipelines over streaming metrics with sub-millisecond SQL queries
TAGS
time-seriesdatabasesqlanalyticsreal-timestreamingcolumnarobservability