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of organizations seek open-source data platforms to eliminate silos and foster interoperability across analytics, AI, and operational workloads
report faster data product development cycles using modular, open-source components tailored to domain-specific needs
faster adoption of AI/ML use cases when leveraging unified, schema-flexible data layers built with open standards and APIs
achieve improved cost efficiency and platform extensibility with community-supported tools and no vendor licensing overhead
XenonStack’s Open-Source Data Platform empowers organizations with a unified, composable architecture that seamlessly integrates data lakes, warehouses, and streams
Unify batch pipelines, streaming events, and unstructured assets under a single, extensible architecture
Use community-backed standards like Iceberg, Kafka, and Trino to ensure interoperability, transparency, and vendor independence
Deliver low-latency insights through streaming frameworks and on-demand querying across massive datasets
Support distributed deployments across cloud, hybrid, and edge setups—centrally governed and fully observable
Mix and match open-source tools to create a tailored ecosystem without vendor lock-in
Govern your data proactively with lineage tracking, data catalogs, and schema versioning
Enable data engineers with APIs, declarative configs, and GitOps-style automation
Gain visibility into compute and storage costs, usage trends, and optimization opportunities
Integrate with BigQuery, GCS, and Vertex AI using open connectors and Kubernetes-native orchestration
Utilize Glue, Athena, and Lake Formation with support for Iceberg, S3, and open table formats
Run data workloads on ADLS, Synapse, and AKS using hybrid-compatible open data tooling
Enforce access controls, audit trails, and data classifications across all layers
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Deliver governed self-service analytics with universal access across BI and reporting tools
Build a solution stack that fits your current needs and evolves with your data maturity
Run your platform seamlessly across public cloud, private cloud, and edge compute environments
Visualize system health, pipeline freshness, and query performance in real time
Adopt end-to-end security practices—from encrypted storage to fine-grained identity and access policies
Empower teams with Git-based workflows, declarative configurations, and CI/CD for data infrastructure
Open-Source Data Platforms offer organizations flexibility, transparency, and cost-efficiency in managing and analyzing data at scale
Explore how cloud-native architectures unify Data Warehouse and Data Lake capabilities to deliver scalable, cost-efficient, and real-time data platforms optimized for AI, analytics, and operational agility
Understand the core components and advantages of a modern Big Data Platform — including scalability, fault tolerance, multi-source integration, and support for batch and stream processing
