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Onehouse
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Onehouse
@Onehousehq
Onehouse is the universal data lakehouse, offering a cloud-native managed lakehouse built on @apachehudi, accessible across table formats, engines and clouds.
Sunnyvale, CA
onehouse.ai
Joined September 2021
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    Onehouse
    @Onehousehq
    Jun 26, 2024
    🎉 Exciting News! For Onehouse and those rooting for the open data lakehouse 🎉 We are happy to announce our $35M Series B round of funding, led by @craft_ventures. The new funding adds more fuel to the Onehouse rocketship, accelerating how we redefine the cutting-edge of
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    Onehouse
    @Onehousehq
    Apr 21
    What does compaction, cleaning, and clustering look like when you operate at Uber scale? At OpenXData, Uber engineers Vamshi Pasunuru and Xinli Shang will share how their team built scalable table services to balance ingestion latency with query performance, and how they
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    Onehouse
    @Onehousehq
    Apr 15
    Meta. Lyft. Amazon. Tosh Rayadhurgam has worked on AI and ML platforms at serious scale. What happens when non-deterministic agents enter such systems? That is what he will unpack at #OpenXData. Most data architectures still assume queries are deterministic. Same query in,
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    Onehouse
    @Onehousehq
    Apr 10
    If you're building shared streaming infrastructure at scale, this talk is for you. ⚙️ Revanth Chandupatla, Principal Engineer at Walmart, has built batch and streaming platforms at multi-petabyte scale. At OpenXData, he’ll share how Walmart built a multi-tenant, multi-cloud
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    Onehouse
    @Onehousehq
    Apr 8
    Chang She helped build pandas. Now he's arguing that the usual data stack starts to break once training data stops looking like tables. 🧠⚙️ At OpenXData, the @lancedb CEO will walk through why exploration, curation, feature engineering, and GPU loading still live in separate
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    Onehouse
    @Onehousehq
    Apr 6
    Ruiyang Wang works on pretraining infrastructure at Anthropic. If he says PDFs belong in your threat model, that should get your attention. 🛡️⚠️ At #OpenXData, Ruiyang is laying out a rasterize-first architecture for safe PDF processing at scale: sandbox the file, render it to
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    Onehouse
    @Onehousehq
    Mar 24
    Announcing Quanton Kubernetes Operator for Apache Spark 🚀 33% organizations adopt Spark on Kubernetes, and now you can get performance you need on infrastructure you control with zero code changes.
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  • Onehouse reposted
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    Vinoth Chandar
    @byte_array
    Mar 24
    💥 Launching Quanton Kubernetes Operator for Apache Spark Spark on k8s hitting 33% adoption—trailing Databricks (47%)—but perf tradeoffs sting. 🛑 It standardizes compute with observability/security, cutting costs 50-70% via discounts. 💸 Catch? Vanilla OSS Spark—slow jobs,
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    Onehouse
    @Onehousehq
    Mar 10
    Onehouse is now officially available on Microsoft Azure. The #1 demand from data teams ever since we announced our faster Spark engine “Quanton” has been Azure support. We are thrilled to answer that call and bring the Onehouse open data lakehouse platform to Azure users – with
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    Onehouse
    @Onehousehq
    Feb 17
    Onehouse LakeBase™ - The first lakehouse serving layer with database capabilities like indexing and caching. Built for machines + humans. Handling high-QPS, low-latency queries from AI agents and heavy analytics. onehouse.ai/blog/announcin…
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    Onehouse
    @Onehousehq
    Jan 26
    If you've got half-committed writes staring back at you like a crime scene in your data lake we need to talk... "The Apache Spark Job That Wouldn’t Retry" 📅 Jan 29, 2026 | 10 AM PT ZOOM 🔗 : onehouse.ai/webinar/the-ap…
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    Onehouse
    @Onehousehq
    Jan 14
    🔁 If you’ve ever rerun a Spark job and thought “please don’t make this worse,” this is for you. We'll show you the patterns that make reruns safe by design: • Know what actually succeeded (explicit state) • Prevent accidental downstream triggers (dependency gating) •
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    Onehouse
    @Onehousehq
    Jan 8
    How to end up with a data swamp: “Let’s just land everything in the lake and figure it out later.” Schema-on-read is powerful. But it has a hidden bill: • No native indexing • No ACID by default • Governance becomes a tooling project • Equality lookups turn into file
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