Apache Doris

📣 Apache Doris 3.0 is now available! With the latest version being 3.0.2, we think maybe it's a good time to announce the advent of Apache Doris 3.0 😆 We've been busy communicating with the many users who have been eagerly awaiting version 3.0, and now we finally have the time to share this news with everybody! 🎉 If we can only use one keyword to describe 3.0, it would be Compute-Storage Decoupling. Starting from version 3.X, Apache Doris supports a compute-storage decoupled mode in addition to the compute-storage coupled mode for cluster deployment. With the cloud-native architecture that decouples the computation and storage layers, users can achieve physical isolation between query loads across multiple compute clusters, as well as isolation between read and write loads. Additionally, users can take advantage of low-cost shared storage systems such as object storage or HDFS to significantly reduce storage costs. Any questions regarding Apache Doris 3.0 is welcomed in our Slack community: https://lnkd.in/ghMuVZW2 https://lnkd.in/gvrWdKys #releasenote #opensource #ApacheDoris #database #dataengineering #dataanalysis

Recently, we’ve received numerous inquiries about the log analysis capabilities of Apache Doris, with many users exploring it as an alternative to the #ELK stack and #OpenSearch. For those interested in this area, we recommend taking inspiration from MiniMax—the team behind Talkie, the phenomenal AI chatbot. They utilize Doris to build a petabyte-scale log analysis system that supports all their business lines. https://lnkd.in/ggqZsxd2 For more specific technical guidance, we encourage you to join the Apache Doris Slack community: https://lnkd.in/ghMuVZW2

User story of Footprint Analytics from the Apache Doris Meetup @Singapore on October 24 📹 https://lnkd.in/gRQc_xv7 Wade Deng, Co-Founder & CTO at Footprint Analytics and XCelsior AI, talked about their blockchain analytics solution using Apache Doris. He started with the introduction to the data platform and architecture of Footprint Analytics, and explained why they chose Apache Doris among options like Apache Druid, ClickHouse, and TiDB. Then he provided lots of hands-on experience and advice on the usage of Apache Doris, including the choice of data models for the crypto domain, materialized view, data migration, and data compaction. "Two years ago, we were using Google Cloud and BigQuery for the major data warehouse. Then we had a few clients who required low latency, especially for our pricing and trading-related tables. We had a few options. In summary, Doris stood out for its high concurrency and SQL support. This lowers the barrier for data scientists and analysts to use our platform." Download the slides from: https://lnkd.in/g7wCwTuv If you have further questions about Apache Doris, join the user community on Slack: https://lnkd.in/ghMuVZW2 #BigData #DataEngineering #Blockchain #ApacheDoris

Q&A of the Apache Doris PMC Chair's talk at OSA CON: ❓ Would you say Apache Doris is mature enough for enterprise use? 🎙️ Yes, Apache Doris has been used in production in thousands of companies, including many industry giants. The stable versions of Doris has stood the test of many enterprise users in their real-life use cases. There are also enterprise-grade commercial offerings based on Apache Doris. ❓ Can Doris write to data lake formats like Iceberg or Delta Lake? 🎙️ Yes, Doris supports writing Iceberg format directly. Currently it supports appending data and we are working on data deletion, upsert, sorting, and compaction. ❓ Where can we read more about what makes Doris performant? Last slide was very good. 🎙️ We've publicized our benchmarking processes and results on our website, and we are constantly sharing the developers' technical insights in our blogs. https://lnkd.in/gTbZ-wgN https://lnkd.in/gZWsfruR ❓ Is there support for data governance within Doris? 🎙️ We are working with Catalog projects such as Apache Gravitino (incubating) for data governance. https://lnkd.in/gs_BBjv2 Watch replay on Airmeet: https://lnkd.in/gmJt_rdH Find "Apache Doris: an alternative lakehouse solution for real-time analytics" in the schedule (Nov. 20) If you want more details of the above topics or have any other questions about Apache Doris, we invite you to join our Slack community. We will be happy to talk to you! 😀 🙌

User story in #blockchain 🌟 Special thanks to Justin Trollip, Founder of Ortege AI, for sharing his hands-on experience in using Apache Doris as the backbone of Ortege's data lakehouse, which handles massive volumes of blockchain data.💡 He writes down his best practices in a few posts and we are happy to reshare them for the benefit of of more users. 🙌 Scaling Bitcoin data to billions of records with Apache Doris: our journey to auto-partitioning https://lnkd.in/gzJyeZsv Fine-tuning Apache Doris for maximum performance and resilience: a deep dive into fe.conf https://lnkd.in/gRdp597V

User story of a livestream e-commerce giant from the Apache Doris Meetup @Singapore on October 24 📹 https://lnkd.in/gZesFQvJ Boyang Chen, a database development engineer and an Apache Doris Contributor, introduced the usage of Doris in Douyin Group and discussed multi-stream data analysis as a common use case based on Doris: "I would use three keywords to describe the Doris usage inside Douyin Group." "The first keyword is real-time data warehouse. As Doris provides powerful ELT ability and efficient query performance, we've been building a real-time data warehouse based on Doris. It mainly consists of two platforms: a data integration platform that controls the data imports and exports of Doris and a data production platform which provides task scheduling." "The second keyword is data serving. As Doris can provide high-QPS and low-latency data analysis, we can use it as a computing engine for multiple business lines, like live streaming, e-commerce, and advertisement." "The last keyword is data lake. As Doris provides powerful data lake ability, we've been using Doris-on-Elasticsearch and Doris-on-Hive. In short, we've been using Doris extensively inside our Group." Download the slides from: https://lnkd.in/gz6yZ9WT If you have further questions about Apache Doris, join the user community on Slack: https://lnkd.in/ghMuVZW2

Enjoying Rayner's talk on #OSACON about Apache Doris as a data lakehouse solution! Come join us for some real-time interaction 🙌 https://lnkd.in/gR86Mvvt #opensource #bigdata #analytics #lakehouse

📣 24-hour countdown for the Apache Doris PMC Chair's talk on OSA CON! Lakehouse is a big data solution that combines the advantages of data warehouse and data lake, helping users to perform fast data analysis and efficient data management on the data lake. Apache Doris is an OLAP database for fast data analytics. It provides self-managed table format for high-concurrency and low-latency queries, semi-structured data analytics and complex ad-hoc queries, all by using standard SQL. It can also query data from various lake formation such as Apache #Hudi, Apache #Iceberg, Apache #Paimon, etc. You will learn what Apache Doris is, what Doris can do for real-time analytics, and how to build a fast data analysis engine on data lake. Don't miss your chance to engage with Mingyu (Rayner) in real time! https://lnkd.in/gmJt_rdH

Big thanks to Sandeep Devarapalli for his in-depth exploration of Apache Doris and for highlighting its key features. 👍 We encourage users to find out whether Doris is the right fit for their specific use cases and share their experience. For those seeking a general overview of Apache Doris, we recommend starting with this talk given by the Apache Doris PMC Chair: https://lnkd.in/g7byRjp5 For those who have specific questions regarding Doris, we invite you to join the our Slack community. This is where you can engage with other Doris users and meet our support team, who will be happy to provide help and guidance! 🙌 https://lnkd.in/ghMuVZW2

Thanks to everybody involved for making this happen. Let's stay connected and keep sparking inspiration in each other! #opensource #bigdata #dataarchitecture #analytics #OLAP