Eon Data Lake Infrastructure
Unlock analytics and AI from your cloud data
Transform backups, archives, databases, and files into a fully managed data lake. Your cloud data becomes instantly queryable for analytics and AI in open formats like Apache Iceberg and Parquet.
A managed, zero-ETL data lake built on your cloud data
No restores, indexing pipelines, or additional infrastructure required.
Turn historical data into an analytics-ready platform.
No proprietary interface or lock-in.
Query instantly with open formats
Eon stores data directly as standard Apache Iceberg tables, making historical datasets immediately usable across your analytics ecosystem, no proprietary formats or connectors required. Query instantly from Snowflake, Databricks, BigQuery, Athena, Spark, and Trino with zero ETL, using fully compatible Iceberg tables that support schema and partition evolution, snapshot isolation, and time travel.
Bring your own catalog. Keep full control of your data
Eon integrates with your existing data catalog and keeps storage directly accessible through standard IAM roles and native cloud tooling so external engines read the same Iceberg tables Eon manages without proprietary layers or lock-in.
Fully managed with zero infrastructure overhead
Eon automatically manages ingestion, schema evolution, compaction, and catalog optimization, eliminating the need to build pipelines or operate supporting data lake infrastructure. No Spark tuning, indexing systems, or storage lifecycle engineering required.
Built for efficiency and performance at scale
Eon’s storage platform applies cross-dataset deduplication and intelligent compaction to reduce storage footprint and accelerate analytics workloads across backups, archives, and infrastructure datasets. Teams can run analytics directly using Eon managed compute engines (e.g., Spark jobs, SQL queries, and notebook workflows) on optimized storage for faster performance at lower cost.
Ready for AI and agent workflows
Eon transforms cloud data into AI-ready datasets and exposes secure, governed access through the Eon MCP server so teams can deploy agents across current and historical datasets without building pipelines.
Learn more from our experts
Frequently Asked Questions
Eon automatically stores backup, historical, and production cloud data in open formats like Apache Iceberg and Parquet, with metadata cataloged for instant discovery. Teams can query historical environments directly. No restores, ETL pipelines, or exporting data.
Yes. Traditional workflows move data into a data lake before analysis. Eon eliminates that step by making your historical and production cloud data analytics-ready by default, so teams can run queries, investigate incidents, validate recovery points, or support AI workflows directly from historical environments.
Eon works with any engine that supports open table formats like Iceberg or Parquet, including Athena, BigQuery, Databricks, Snowflake, Spark, and Trino. There’s no proprietary interface or lock-in.
No. Backups remain incremental-forever and deduplicated for storage efficiency. Because Eon writes data directly in analytics-ready formats, teams gain query access without additional pipelines, duplicate storage, or restore overhead.
Yes. Analytics access runs against immutable, logically air-gapped storage, not production systems. Eon enforces RBAC, encryption in transit and at rest, and retention policies while supporting compliance requirements like GDPR, HIPAA, and PCI.
Ready to turn passive storage into active infrastructure?
Eon is a self-funding platform delivering immediate ROI and savings.
Enterprise-grade, single-tenant architecture
Each workspace runs inside a dedicated account and VPC, with no shared infrastructure.
