Cost reduction
Unoptimized tables drive up storage and compute—small files, fragmented manifests, and unused snapshots. LakeOps continuously corrects these conditions automatically.
Lower cost without manual cleanup.
Real-time autonomous
data lake optimization
Automate compaction and maintenance in real time. Better performance, lower cost—no scripts, no cron jobs, no guesswork.
80%
lower CPU & storage costs
12×
faster queries
100%
maintenance automation
Runs on your stack
Platform
The control plane for data lakes
End-to-end optimization for every table op, across storage and engines. Telemetry-driven smart orchestration with full visibility and control.
LakeOps
Last 30 days Optimization Activity
Total Operations
12211
successfully run in Last 3 months
Query speed
12.4x
Avg. acceleration across engines
Cost savings
$1,374,672
Saved in last 3 months
CPU & Storage
-76%
Resources saved in last 3 months
Data Optimized
46.8 PB
Volume compacted in last 30 days
Key Metrics
Total Tables
786
Tables in all catalogs
Critical Tables
70
Require Immediate attention
Warning Tables
105
Should be addressed or auto-piloted
Healthy Tables
566
Tables in optimal state
Total Data
112.4 PB
Total lake data size
Recent Operations
Last 10 operations| Operation | Table | Duration | Impact | Time | Status |
|---|---|---|---|---|---|
| Compact Data Files | customer_orders orders | 4s | 1.24 TB, 16 → 1 files | 57 minutes ago | SUCCESS |
| Expire Snapshots | payment_transactions payments | 27s | 8.2 TB | 4 hours ago | SUCCESS |
| Expire Snapshots | inventory_snapshots_20250702 warehouse | 3s | 2.1 TB | 4 hours ago | SUCCESS |
20x Faster compaction
Rust-based compaction engine for Iceberg—optimizes file layout at scale.
Manifest Rewrites
Compact metadata so query planning stays fast across the lake.
Snapshot Optimization
Automated retention and expiration—no manual snapshot hygiene.
Orphan File Cleanup
Detect and remove orphaned files safely. Eliminate storage drift.
Managed Schema Evolution
Schema changes applied safely across engines and workloads.
Table Health Monitoring
Continuous analysis of table structure and optimization opportunities.
Cross-system Telemetry
One source of truth across storage, engines, and catalogs.
Multi-Engine Routing
Optimize for Trino, Spark, Flink, and more in one operational layer.
Native to AI Agents
Built for AI and ML pipelines—optimized metadata and layout for agents.
Full Iceberg benefits. Snowflake-level ease.
Get a personalized walkthrough and see how LakeOps can optimize your data lake.
No vendor lock-inNo infra or data changes10 min to installSecure and compliant
What platform teams say
Trusted by data platform engineers
LakeOps took the pain out of compaction and maintenance. We went from ad-hoc scripts and firefighting to a single control plane. Query performance improved and our platform team finally has visibility across the lake.
Shira B.
Staff Data Platform Engineer
We evaluated several options for Iceberg operations. LakeOps stood out for its focus on automation and multi-engine support. Deployment was straightforward and the impact on cost and latency was measurable within weeks.
Alex M.
Principal Engineer, Data Infrastructure
Our tables were suffering from small files and fragmented metadata. LakeOps runs continuously in the background—we set policies once and the system handles the rest. Maintenance automation that actually works.
Sanjay M.
Director of Data Platform
Enterprise
Scale with LakeOps Enterprise
SOC 2, SSO, RBAC, scale, and dedicated support—for the largest Iceberg lakes.
Security & compliance
SOC 2 Type II, encryption at rest and in transit, RBAC, and audit logs. Built for regulated and high-security environments.
Scale & control
Single control plane for the whole lake. Full visibility and predictable performance at scale.
Trust & ecosystem
Dedicated success manager, SLAs, and SSO. On-prem or VPC deployment when you need it.
Why LakeOps
Why platform teams choose LakeOps
Query performance
Efficient file layout and metadata are critical for query engines. LakeOps keeps file sizes optimal, partitions balanced, and metadata compact.
Queries plan faster and scan less.
Automated maintenance
Manual scripts often fail under concurrent writers and streaming workloads. LakeOps orchestrates maintenance with full awareness of active workloads.
Safe, hands-off maintenance.
Visibility and control
Table health dashboards, compaction insights, maintenance history, cost and performance metrics. Monitor everything while the system handles execution.
Full visibility and control.
AI readiness
AI and ML workloads demand consistent, well-organized data and fast metadata. LakeOps keeps tables optimized for feature stores, model training, and real-time pipelines.
Ready for AI and ML at scale.
Cross-system operability
Works across engines, storage systems, and clouds. One operational layer for Iceberg everywhere—no lock-in, no vendor-specific scripts.
One platform across your entire lake.
Get in touch
See LakeOps on your stack
Short call. Your architecture. We'll show how the control plane fits Snowflake, Databricks, Trino, and your lake—no vendor lock-in.
No commitment · Typically 30 min