Why is the modern data stack undergoing yet another shift with the emergence of #ApacheIceberg? ?? Check out this guide to Iceberg, covering everything you need to know about Iceberg’s rise in popularity and rapid adoption to learn: ? The evolution of on-premise databases to cloud data platforms ? What is a data lake and how does it compare to the lakehouse? ? Use cases for lakes and lakehouses ? Data lake vs. lakehouse architecture? ? File and table formats ? Transactions in the lakehouse ? Schema and partition management ? Scalability and performance in the lakehouse Lakehouse vs. Data Lake: The Ultimate Guide ?? https://lnkd.in/dE_6WtDD Are you just getting started with Iceberg? As the control center for your lakehouse, Upsolver can help you with table management, performance and storage optimization, and data ingestion. If you have an Iceberg project that you need help with, please get in touch at ?? https://lnkd.in/d3UuXaNm #DataLakehouse #DataLake #LakehouseArchitecture #DataEngineering
Upsolver
软件开发
Sunnyvale,California 5,944 位关注者
Bridges the gap between engineering and data teams by streaming and optimizing operational data in an Iceberg lakehouse.
关于我们
We help data developers move data from prod environments to analytics and other downstream use cases at scale and with quality oversight. From structured transactional databases to semi-structured interaction event streams, ingest prod data to warehouses and lakes to unlock value. Data generated by your product applications and services is your biggest lever to delivering differentiated product and user experiences. Upsolver helps you extend your business moat by unlocking the full value of your moat data. Because data that’s uniquely yours provides the best looking glass into how your users benefit from your products and services—and what’s lacking.
- 网站
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https://www.upsolver.com/
Upsolver的外部链接
- 所属行业
- 软件开发
- 规模
- 51-200 人
- 总部
- Sunnyvale,California
- 类型
- 私人持股
- 创立
- 2014
- 领域
- Streaming Data、Real Time Analysis、Big Data、NoSQL、Databases、Data Integration、Data Management、Data Preparation、Machine Learning、Streaming Data、Data Lakes、AWS、Hadoop、data warehouse和change data capture
产品
Upsolver
大数据处理与分发软件
Upsolver is a big data ingestion built on Amazon Web Services to ingest data from streams, files and database sources (CDC) in real time directly to your data warehouse or data lake. It guarantees your data arrives exactly once and is strongly ordered to de-risk downstream data modeling. It's key benefits are: Reliable - Guaranteed exactly-once, strongly-ordered data Observable - Detect and resolve data and schema issues upstream Easy - No-code ingestion for batch and streaming sources Fresh - Up-to-the-minute data in your warehouse and lake
地点
Upsolver员工
动态
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?? Watch the panel discussion from the Chill Data Summit in #London where our data and open-source experts debated the future of #ApacheIceberg. Moderated by Santona Tuli, Ph.D., this conversation dived into the trends, challenges, and innovations shaping the next phase of Iceberg’s evolution. Our panelists included: ? Ryan Dolley, Vice President of Product Strategy at GoodData ? Chris Tabb, Co-Founder & CCO at LEIT DATA ? Hugo Lu, Founder at Orchestra ? Yoni Eini, CTO & Co-Founder at #Upsolver ? JB Onofré, Board Member of The Apache Software Foundation & Principal Software Engineer at Dremio Whether you're an engineer, data architect, or open-source enthusiast, enjoy the diverse industry experiences and opinions shared by our special line-up. Thank you to our awesome speakers for participating ?? ?? Watch the replay here: https://lnkd.in/e5Y-QrPH #ChillDataSummit #ExpertsPanel #Data #Debate
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? Let us introduce you to #ApacheIceberg with the top 10 things every #dataengineer should know about this emerging technology that is transforming our data lakes ? 10 Things You Need to Know About Apache Iceberg ?????? https://lnkd.in/dhu7c3BV #datalakehouse #dataprofessional #bigdata
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?? You still have time to join this highly-anticipated webinar led by Jason Hall, Senior Solutions Architect at Upsolver. ?? Topic: Advanced Concepts in #ApacheIceberg Table Design If you've ever managed high-cardinality columns, data skew, or dense values in Iceberg tables, you know it requires expert adjustments for peak performance. But what if you could automate these steps? In this session, Jason will cover: 1?? The limitations of traditional partitioning, sorting, and clustering. 2?? How high-cardinality data impacts costs and query efficiency. 3?? Upsolver's Adaptive Clustering: a game-changer for dynamic partitioning. ?? Note: Spaces are limited, and interest is high! Don’t miss the chance to upgrade your Iceberg table strategies. ?? Register now to secure your spot! https://lnkd.in/ebu-7_Uk #DataEngineering #CloudArchitecture #DataLakehouse
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At our Chill Data Summit London event, Seda KOCAK, Senior Data Analyst at The Dot Collective, explored how #DataModeling can transform decision-making and system design for today’s organizations. Here’s what Seda shared: ?? Building a Strong Foundation: Effective data models lay the groundwork for reliable systems and insightful decisions, empowering organizations to harness the full potential of their data. ?? Aligning with Business Objectives: By structuring data models to reflect key business goals, analysts and architects ensure that technical solutions drive meaningful, impact-focused analytics. ?? Bridging Strategy with Practice: Seda walked through real-world examples and best practices, illustrating how to merge technical precision with strategic vision—from sharp analytics to actionable insights. Whether you're a data architect, analyst, or engineer, this session is packed with practical guidance for data-driven design. ?? ?? Catch the replay to learn about building impactful data architectures: https://lnkd.in/eCjVHVz9 What was your top takeaway from Seda’s insights? Share below! ?? #DataDriven #SystemDesign #DataArchitecture #BusinessIntelligence
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?? New Release Alert from #ChillDataSummit in #London! Dive into this session with Santona Tuli, Ph.D. as she unpacks the power of Change Data Capture (CDC) in #ApacheIceberg and why it’s a game-changer for real-time data processing. ?? Picture this: an agile data environment where updates are seamless, analytics are instant, and your pipelines don’t skip a beat ?? Here’s what Santona covered: ?? Essential use cases for CDC ?? Top technical insights for data-centric teams ?? Pro tips for efficient CDC implementation Data engineers, architects, and pipeline designers – this one’s for you. Don’t miss these takeaways! ?? Watch the full replay here: https://lnkd.in/eEwwEaP3 Let’s talk! What’s your biggest challenge in keeping real-time data in sync? Drop a comment below. ?? #DataEngineering #DataIngestion #CDC
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Check out this session from Jan Kaul, Founder and CEO at Dashbook, as he takes a deep dive into analytical data transformations using #ApacheIceberg materialized views ?? Recorded live at the #ChillDataSummit in #London, this talk is packed with valuable insights. Jan demonstrates how Apache Iceberg's materialized views simplify and enhance data transformations, streamlining analytical workloads for a smoother, more efficient experience. Learn about the technical foundations, best practices, and practical applications that make Iceberg materialized views essential for scalable data transformation. Catch the video here ?? https://lnkd.in/evrdcXA2 #DataEngineering #CloudArchitecture #DataLakehouse
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?? Ready to build an #ApacheIceberg lakehouse that delivers consistent performance, reliability, and ease of use? Join us for a live webinar TODAY that walks you through each stage of planning and executing your project. ?? Online ??? Wednesday November 13th ? 10am PT / 1pm ET / 5pm GMT ?? From Blueprint to Success: Planning Your Iceberg Lakehouse Project Here’s a sneak peek at what you’ll learn: ? Maximizing Performance: Explore how Iceberg enables consistent performance, reliability, and simplicity across a wide range of query and processing engines. ? Simplifying the User Experience: Learn how schema evolution, time travel, and hidden partitions simplify the user experience without sacrificing performance or cost savings. ? Unifying Access with Iceberg Catalogs: See how Apache Polaris Catalog and other Iceberg-compatible catalogs are breaking barriers for more users to securely access data from their tools of choice. ? Effortless Table Management with Adaptive Optimizer: Discover how Adaptive Optimizer for Apache Iceberg boosts query performance by over 2.5x and reduces storage costs by up to 50%, all while eliminating manual table management. Upsolver's Principal Solutions Architect, Ajay Chhawacharia, will be leading this webinar and sharing his real-world expertise. Bring a coffee and any questions for Ajay, and enjoy this informative session ?? Register here: https://lnkd.in/gJNnDhJ9 #DataLakehouse #DataEngineering #CloudArchitecture
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?? Join us for this highly-anticipated webinar led by Jason Hall, Senior Solutions Architect at Upsolver. ?? Topic: Advanced Concepts in #ApacheIceberg Table Design If you've ever managed high-cardinality columns, data skew, or dense values in Iceberg tables, you know it requires expert adjustments for peak performance. But what if you could automate these steps? In this session, Jason will cover: 1?? The limitations of traditional partitioning, sorting, and clustering. 2?? How high-cardinality data impacts costs and query efficiency. 3?? Upsolver's Adaptive Clustering: a game-changer for dynamic partitioning. ?? Note: Spaces are limited, and interest is high! Don’t miss the chance to upgrade your Iceberg table strategies. ?? Register now to secure your spot! https://lnkd.in/erwKjwxE #DataEngineering #CloudArchitecture #DataLakhouse
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? JB Onofré kicked off our #ChillDataSummit in London with an insightful talk on the future of #ApacheIceberg and Apache Polaris (Incubating), and now you can watch it online! ?? As Principal Software Engineer at Dremio and a Board Member of The Apache Software Foundation, JB shared his expertise on the evolving components of the data lakehouse. He discussed how advancements in query engines, catalogs, table formats, and storage layers are shaping a more open, adaptable data ecosystem. JB broke down each layer, highlighting the performance boosts Iceberg already delivers to data lakes and exciting updates on the horizon, including the REST specification. Catch his talk here ?? https://lnkd.in/e8B9MG9N #DataEngineering #DataLakehouse #DataArchitecture