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.
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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.
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AI-powered observability and optimization for Hadoop and big data environments.
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An open-source data platform for Hadoop modernization, flexibility, and long-term control.
Runtime Visibility, Compute Control, fewer SLA Failures for enterprise-grade pipelines on your infrastructure — it's more than just success metrics.


Most pipelines fail silently. xLake closes that gap.
DAGs succeed while Spark jobs silently consume 3× expected resources and downstream tasks queue behind them
You can't see which queries are creating contention in the 8 PM scheduling window, only that something went wrong afterward
Platforms that handle orchestration for you do it on their infrastructure, at their pricing, under their constraints
Legacy platforms hit concurrency limits you're now engineering around manually
Spark, Trino, and Python workloads each need separate tooling, separate logging, separate everything
xLake deploys directly onto your Kubernetes clusters — EKS, AKS, GKE, or on-premises. Your data stays in your environment. Your compute plane stays under your control.
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More than just DAG Success Status. xLake answers questions that actually matter:

Describe a pipeline in plain language. Upload an existing YAML or SQL spec. xLake generates the DAG. Your engineer reviews, adjusts, and ships.

Every cost driver that legacy platforms obscure or ignore — surfaced and resolved.
Where pipeline failure is a business problem. Where a missed SLA has a cost. Where teams are accountable for both reliability and efficiency.
For teams managing dozens of concurrent pipelines across hybrid environments and hitting the limits of what your current orchestrator can observe and legacy platforms can scale — xLake is built for this.
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