VeloDB

This is the first of a series of webinars to present to you the capabilities of Apache Doris and its enterprise-grade offering in various use cases. We will start with real-time analytics and gradually cover data lakehousing, log management and analysis, and many of its game-changing features. Our goal is to help users figure out how Doris can benefit their use case and how to make the most out of Doris. For the upcoming online webinar, we are excited to welcome Colin Wang, an Apache Doris contributor and now a Product Manager at VeloDB, to share his understandings of Doris. As a previous Solution Architect, Colin has years of experience in assisting Doris users in production environment and accumulated valuable user-oriented insights. His talk will cover: 🎙️ Introduction to Apache Doris' capabilities for real-time analytics, from data imports to queries and fast data changes 🎙️ Real-time data ingestion and storage 🎙️ Features to enable lightning response to real-time data services and interactive data analysis 🎙️ Pre-aggregation and real-time joins 🎙️ Features to support high-concurrency queries (10K QPS per node) 🎙️ Functional comparison with #ClickHouse, #Druid, #Pinot, #Redshift, #Snowflake, and #Elasticsearch 🎙️ Building a real-time data pipeline with Apache Doris 🎙️ Real-life use cases Click the Attend button, mark your calendar, and share the link with friends who might be interested. It's going to be a fruitful session!

How does Apache Doris deliver lightning-fast query responses for massive datasets? The secrets are: 1️⃣ Vectorization: something that works beneath the surface for you 2️⃣ Cost-based optimizer (CBO): something that is continuously improved with each release 3️⃣ Indexes: something powerful and diverse to choose from 4️⃣ Materialized view: something you can utilize and design specifically for your case Revisiting key insights from the VeloDB webinar on 🌟 Real-Time Analytics with Apache Doris: Everything You Need to Know Watch replay: https://lnkd.in/gts6CkpA

Revisiting key insights from yesterday's webinar on 🌟 Real-Time Analytics with Apache Doris: Everything You Need to Know The data ingestion methods supported by Apache Doris and their performance are summarized as follows: Full HD video available on YouTube: https://lnkd.in/gts6CkpA #analytics #bigdata #dataimport #datapipeline

Calling all data and open-source enthusiasts in Singapore: Join the Apache Iceberg Community Meetup next Wednesday! https://lu.ma/79xk5w5t Rayner Chen, Vice President of Technology at VeloDB and also the Apache Doris PMC Chair, will give a talk on: 🎙️ Building Fast Data Lake Analysis on top of Apache Iceberg & Apache Doris Other Topics: 🎙️ Xinyu Zhou (Co-Founder & CTO at AutoMQ) - AutoMQ Table Topic: Bridging Streaming and Analytics with Iceberg 🎙️ Jay Chia (Co-Founder at Eventual Daft) - Iceberg in Python 🕔 5PM~8PM (GMT+8), December 18 🌏 16 Collyer Quay, Level 12 December 18 is going to be a day filled with sparkling tech ideas because it also marks the first VeloDB live webinar: 🎙️ Real-Time Analytics with Apache Doris: Everything You Need to Know Join us online: https://lnkd.in/g4jeZvHt #opensource #bigdata

Apache Doris 3.0.3 is now available! See what's new: 🌟 Support for deploying the Compute-Storage Decoupled mode on #ARM 🌟 A new variable to control the control the affinity of cold and hot tiered replicas 🌟 Added syntax for querying partition information of #Hive tables 🌟 Support for the creation of Hive tables in Text format 🌟 Support for the correlation of non-aggregate subqueries 🌟 Improved file caching to increase hit rate and high-concurrency query performance 🌟 Support for reading Hive tables in #OpenCSV format ... Check the full list and download for a spin! 🙌 https://lnkd.in/gpQVMvKu #opensource #dataengineering #dataplatform #releasenote #bigdata #OLAP #analytics

Session recording 📹: ZHI LIU Product Manager at RisingWave discussed real-time data enrichment and analytics using RisingWave and Apache Doris: "Streaming process and OLAP are not like a one-to-replace-the-other relationship. It's more like: Each of the processing paradigm tries to solve a different use case. So when people first come up with stream processing, they ask the question like: In real world, data is generated continuously, so why don't we process data continuously so that we can acquire insights continuously? The idea is that you are facing an infinite stream of data where you have a fixed query, so whenever there are new data coming to the system, the query reacts to the data." "The idea of OLAP is more like: You have a finite set of data, and business analysts will try to explore what's contained in that data set, so they will come up with different queries. Based on the insights, the modify the queries and try to get more different insights." https://lnkd.in/ghRPu4-X With this, we’ve wrapped up all sessions from the Apache Doris Meetup @Singapore! If you’re still eager to connect with the Apache Doris community, don’t miss the upcoming online webinar. Colin Wang will provide an in-depth introduction to 🌟Real-Time Analytics with Apache Doris: Everything You Need to Know 🌟. Stay tuned and join us! https://lnkd.in/g4jeZvHt

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

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

We are expanding our team! 📣 We currently have 6 job openings and are in search of talented candidates in Silicon Valley and Singapore. 1️⃣ North America General Manager 2️⃣ Marketing Director 3️⃣ Database Post-Sales Engineer (SaaS) 4️⃣ Solution Architect 5️⃣ Product Manager 6️⃣ Business Developer Please send your resume to contact@velodb.io We can’t wait to learn more about you and explore the possibility of working together! https://lnkd.in/g6s4pVy8 #bigdata #jobs

Talks from the Apache Doris Meetup @Singapore on October 24: Mingyu (Rayner) Chen, the Apache Doris PMC Chair introduces Apache Doris, covering its application scenarios and the technical implementation that powers it, highlighting Doris' fast performance, user friendliness, and capabilities to handle different types of analytics workloads: “Apache Doris is friendly for first-time users, with a low operational cost as a distributed system and flexible deployment operation for various environments. Besides reporting and ad-hoc analysis, Doris also supports semi-structured data analysis and can act like a lakehouse query engine. ” "For both single-table query and complex multi-table joins, Apache Doris can give better performance than other alternatives." "Tencent Music, a leading online provider, replaced Elasticsearch with Doris so they can unify their online data analysis and their user content retrieval service. It reduced their storage usage by 80% and improved their data freshness by reducing the data import time from 10 hours to 3 hours." Full video: https://lnkd.in/g7byRjp5