Integrate Time Series with Data Lakes and Warehouses

Built for data teams

What is open data access and how does it work?

Bring specialized time series data handling and real-time analytics to your operations data and enable zero-copy, no-ETL data sharing and interoperability with your existing data lakehouses and warehouses. Bridge the gap between real-time operations and analytical data tools, including lakehouses, by virtualizing data access to InfluxDB with Apache Iceberg.

InfluxDB offers high-performance data ingestion, real-time querying, and built-in functions for time series analysis. It persists data on commodity storage in an open file format known as Apache Parquet, and its catalog is abstracted to enable data access virtualization via an open table format, such as Apache Iceberg, Delta-sharing, etc.

Real-time operational analytics

InfluxDB’s columnar, in-memory tier enables sub-second query responses so you can power real-time use cases like operational event analytics, threat monitoring, gaming analytics, and more.

Hybrid data persistence

Time series data at scale can accumulate quickly, leading to massive datasets with cardinality concerns. InfluxDB is optimized for efficient storage and partitioning strategies to handle time series data at any scale and cardinality. Leverage InfluxDB for time series operational workloads while using data access virtualization to train AI/ML models and run advanced analytics in your existing data lakehouses.

Lower total cost of ownership

Data access virtualization allows direct data access to Parquet files without any data movement or need to hold multiple copies of the data, which helps lower costs by reducing replication, transfer, and storage costs. The lack of any ETL increases operational efficiency, so you can do more while using fewer resources.