Everything you need to build, govern, and scale data and AI workloads—one unified platform.
Monitor, detect, and resolve data and AI issues with end-to-end observability across pipelines.
Build, orchestrate, and run data pipelines with intelligent agents that automate the entire engineering workflow.
Query your lakehouse in-place with Velox-accelerated performance. 10x faster than traditional warehouses.
Distributed training, high-throughput inference, and GPU notebooks—everything you need for production AI.
Build, deploy, and manage intelligent agents to automate and optimize data operations.
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
Browse solutions to help you solve the complex business challenges unique to your industry.
"PhonePe’s data infrastructure reliability initiative would never have been possible without Acceldata.”
Browse materials to help you access the tools, guides, and insights essential to your workflows.
How to assess AI data readiness across four stages.
Learn about our mission, leadership, and vision driving modern data operations forward.
How to assess AI data readiness across four stages.
Browse solutions to help you solve the complex business challenges unique to your industry.
"PhonePe’s data infrastructure reliability initiative would never have been possible without Acceldata.”
Browse materials to help you access the tools, guides, and insights essential to your workflows.
How to assess AI data readiness across four stages.
Learn about our mission, leadership, and vision driving modern data operations forward.
How to assess AI data readiness across four stages.
Everything you need to build, govern, and scale data and AI workloads—one unified platform.
Monitor, detect, and resolve data and AI issues with end-to-end observability across pipelines.
Build, deploy, and manage intelligent agents to automate and optimize data operations.
Build, orchestrate, and run data pipelines with intelligent agents that automate the entire engineering workflow.
Query your lakehouse in-place with Velox-accelerated performance. 10x faster than traditional warehouses.
Distributed training, high-throughput inference, and GPU notebooks—everything you need for production AI.
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse sollicitudin mi
Monitor, detect, and resolve data issues with end-to-end observability across pipelines.
Monitor, detect, and resolve data issues with end-to-end observability across pipelines.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse sollicitudin mi nibh
AI-powered observability and optimization for Hadoop and big data environments.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse sollicitudin
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse so
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
xLake consolidates Spark, Trino, and Jupyter under a single control plane — on your Kubernetes cluster, inside your VPC, on your terms.



xlake runs Spark Java, Spark Python, Notebook, and Trino jobs from a single Jobs dashboard — not per-engine consoles bolted together.
Spark for batch. Trino for queries. Jupyter for exploration. Three engines, three job UIs, three operational overhead streams — and zero unified visibility.
xLake installs into your existing Kubernetes namespace. No proprietary runtime. No infrastructure replacement. No external control plane.
Standard Kubernetes constructs only — namespaces, resource quotas, node pools. Nothing proprietary.
Write standard SQL. xLake's Trino engine builds an optimized distributed execution plan across every registered catalog.
Access controls and catalog visibility are evaluated at the query layer — natively — before a single byte is read.
Queries run on your Kubernetes clusters — EKS, AKS, GKE, or on-prem K8s 1.20+. You control resource limits and cost ceilings.
Results go directly to the requesting system. No intermediate copies. No sync jobs. No replication pipelines.
Query history and execution logs capture which catalogs and nodes handled each stage. Deeper observability added via Pulse observability integration.


Every cost driver that legacy platforms obscure or ignore — surfaced and resolved.
No. xLake is designed so that engineers and data practitioners can describe pipeline intent in plain language — what data to move, how to transform it, and where it should land. xLake handles all code generation. Knowledge of Spark syntax or orchestration frameworks is not required to author a production-ready pipeline.
Agents detect and resolve issues proactively, maintaining SLAs even when pipelines fail.
Yes—trust agents validate data early in the workflow, reducing errors downstream.
ADM works with Airflow, Snowflake, Databricks, and more—enhancing your stack without disruption.
Governance agents enforce policy and traceability across workflows—supporting GDPR, HIPAA, ESG, and more.
Customers typically see 30–50% faster workflows and 80% fewer quality incidents.
Products
Data & AI ObservabilityAgentic Data EngineeringCost OptimizationData WarehousingAgentic RuntimeAgentic Data ManagementData Platform ModernizationPlatform
Platform OverviewGet CertifiedCapabilities
PlanningAnomaly DetectionObservabilityDiscoveryCompare Acceldata
Acceldata vs ClouderaAcceldata vs Monte Carlo DataAcceldata vs BigeyeAcceldata vs DQ LabsAcceldata vs AnomaloAcceldata vs SlingshotAcceldata + Collibra