| /* |
| Used by ContentWidget.js in index.js to display the first 5 entries from the top. |
| */ |
| |
| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| |
| |
| export const Content = [ |
| { |
| "date": "2023-09-07", |
| "title": "New in Apache Druid 27: Querying Deep Storage", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2023/09/07/new-in-apache-druid-27-querying-deep-storage/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2023-08-29", |
| "title": "Using Druid with MinIO", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2023/08/29/using-druid-with-minio/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2023-06-28", |
| "title": "Indexes in Apache Druid", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2023/06/28/indexes-in-apache-druid/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2023-04-23", |
| "title": "Multi-Value Dimensions in Apache Druid (Part 5)", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2023/04/23/multivalue-dimensions-in-apache-druid-part-5/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2023-04-08", |
| "title": "Druid Sneak Peek: Timeseries Interpolation", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2023/04/08/druid-sneak-peek-timeseries-interpolation/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2023-03-07", |
| "title": "Selective Bulk Upserts in Apache Druid", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2023/03/07/selective-bulk-upserts-in-apache-druid/", |
| "company": "Imply" |
| }, |
| |
| { |
| "date": "2023-01-27", |
| "title": "Primary and secondary partitioning", |
| "name": "Sergio Ferragut", |
| "link": "https://imply.io/blog/real-time-analytics-database-uses-partitioning-and-pruning-to-achieve-its-legendary-performance/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2023-01-27", |
| "title": "Using Apache Druid for analyzing streaming data", |
| "name": "Julia Brouillette", |
| "link": "https://devops.com/stream-big-think-bigger-analyze-streaming-data-at-scale/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2022-12-15", |
| "title": "Why Confluent analyzes Kafka streams with Druid", |
| "name": "Matt Armstrong", |
| "link": "https://www.youtube.com/watch?v=Bozxc3vP1PA", |
| "company": "Imply" |
| }, |
| { |
| "date": "2022-12-14", |
| "title": "Support for nested JSON columns in Druid", |
| "name": "Karthik Kasibhatla", |
| "link": "https://imply.io/blog/native-support-for-semi-structured-data-in-apache-druid/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2022-12-02", |
| "title": "Apache Druid's fit in the modern data stack", |
| "name": "David Wang", |
| "link": "https://imply.io/videos/apache-druids-fit-in-the-modern-data-stack/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2023-01-22", |
| "title": "Apache Druid: Data Lifecycle Management", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2023/01/22/apache-druid-data-lifecycle-management/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2022-03-20", |
| "title": "Druid Data Cookbook: Quantiles in Druid with Data Sketches", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2022/03/20/druid-data-cookbook-quantiles-in-druid-with-datasketches/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2022-02-09", |
| "title": "Druid Data Cookbook: Ingestion Transforms", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2022/02/09/druid-data-cookbook-ingestion-transforms/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2022-02-04", |
| "title": "Multi-dimensional range partitioning", |
| "name": "Kashif Faraz", |
| "link": "https://imply.io/blog/multi-dimensional-range-partitioning/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2021-12-16", |
| "title": "Seeking the Perfect Apache Druid Rollup", |
| "name": "Neil Buesing", |
| "link": "https://www.rilldata.com/blog/seeking-the-perfect-apache-druid-rollup", |
| "company": "Rill Data" |
| }, |
| { |
| "date": "2021-11-08", |
| "title": "Scaling Apache Druid for Real-Time Cloud Analytics at Confluent", |
| "name": "Harini Rajendran, Zohreh Krimi", |
| "link": "https://www.confluent.io/blog/scaling-apache-druid-for-real-time-cloud-analytics-at-confluent/", |
| "company": "Confluent" |
| }, |
| { |
| "date": "2021-10-01", |
| "title": "Setting up Apache Druid on Kubernetes in under 30 minutes", |
| "name": "Adheip Singh", |
| "link": "https://www.rilldata.com/blog/setting-up-apache-druid-on-kubernetes-part-one", |
| "company": "Rill Data" |
| }, |
| { |
| "date": "2021-09-25", |
| "title": "Multi-Value Dimensions in Apache Druid (Part 3)", |
| "name": "Hellmar Becker", |
| "link": "https://blog.hellmar-becker.de/2021/09/25/multivalue-dimensions-in-apache-druid-part-3/", |
| "company": "Imply" |
| }, |
| { |
| "date": "2021-09-08", |
| "title": "Anomaly detection using Druid and Imply Pivot", |
| "name": "Vijay Narayanan", |
| "link": "https://vijay-narayanan-bigdata.medium.com/anomaly-detection-using-druid-and-imply-pivot-d6cd5bf158db", |
| "company": "Imply" |
| }, |
| { |
| "date": "2021-08-16", |
| "title": "Druid: Event-Driven Data with Eric Tschetter", |
| "name": "Jeff Meyerson", |
| "link": "https://softwareengineeringdaily.com/2021/08/16/druid-event-driven-data-with-eric-tschetter/", |
| "company": "SE Daily" |
| }, |
| { |
| "date": "2021-08-18", |
| "title": "Augmented analytics on business metrics by Cuebook with Apache Druid", |
| "name": "Sachin Bansal", |
| "link": "https://imply.io/post/augmented-analytics-on-business-metrics-by-cuebook", |
| "company": "Cuebook" |
| }, |
| { |
| "date": "2021-08-11", |
| "title": "Was ist Apache Druid?", |
| "name": "Stefan Luber", |
| "link": "https://www.bigdata-insider.de/was-ist-apache-druid-a-1044465/", |
| "company": "Big Data Insider" |
| }, |
| { |
| "date": "2021-08-09", |
| "title": "Funnel Analysis with Spark, Druid and DataSketches", |
| "name": "Itai Yaffe, Yakir Buskila", |
| "link": "https://youtu.be/dOBb0IOdsnU", |
| "company": "Databricks Data and AI Summit 2021" |
| }, |
| { |
| "date": "2021-07-26", |
| "title": "Apache Druid Deep Dive", |
| "name": "Jon King", |
| "link": "https://youtu.be/TkARXVqDvEw", |
| "company": "RVA Data Engineering" |
| }, |
| { |
| "date": "2021-07-21", |
| "title": "Apache Druid – Datenspeicher mit geringen Latenzen", |
| "name": "Thomas Joos, Nico Litzel", |
| "link": "https://www.bigdata-insider.de/apache-druid-datenspeicher-mit-geringen-latenzen-a-1034042/", |
| "company": "Big Data Insider" |
| }, |
| { |
| "date": "2021-06-17", |
| "title": "Casting the spell: Druid in Practice", |
| "name": "Itai Yaffe, Yakir Buskila", |
| "link": "https://youtu.be/QAitmv8QRq4", |
| "company": "Berlin Buzzwords 2021" |
| }, |
| { |
| "date": "2021-06-07", |
| "title": "Intro to Apache Druid … What is this Devilry", |
| "name": "Daniel Beach", |
| "link": "https://www.confessionsofadataguy.com/intro-to-apache-druid-what-is-this-devilry/", |
| "company": "Confessions of a Data Guy Blog" |
| }, |
| { |
| "date": "2021-02-22", |
| "title": "Data Modeling and Query Performance in Apache Druid", |
| "name": "Matt Sarrel", |
| "link": "https://www.druidforum.org/t/data-modeling-and-query-performance-in-apache-druid/5942", |
| "company": "Imply" |
| }, |
| { |
| "date": "2020-04-16", |
| "title": "Apache Druid Vision and Roadmap", |
| "name": "Gian Merlino", |
| "link": "https://youtu.be/IhqDsoIHqWY", |
| "company": "Imply" |
| }, |
| { |
| "date": "2020-04-16", |
| "title": "Automating CI/CD for Druid Clusters at Athena Health", |
| "name": "Shyam Mudambi, Ramesh Kempanna and Karthik Urs", |
| "link": "https://youtu.be/XGzMJBM8xeg", |
| "company": "Athena Health" |
| }, |
| { |
| "date": "2020-04-13", |
| "title": "Holistic AML compliance using Apache Druid", |
| "name": "Arpit Dubey", |
| "link": "https://youtu.be/Ly3HFbbEihQ", |
| "company": "DBS" |
| }, |
| { |
| "date": "2020-04-13", |
| "title": "How Apache Druid Powers Real-Time Analytics at BT", |
| "name": "Pankaj Tiwari", |
| "link": "https://youtu.be/QZUunUDQ8p4", |
| "company": "BT" |
| }, |
| { |
| "date": "2020-04-13", |
| "title": "Analytics over Terabytes of Data at Twitter using Apache Druid", |
| "name": "Swapnesh Gandhi", |
| "link": "https://imply.io/virtual-druid-summit/analytics-over-terabytes-of-data-at-twitter-apache-druid", |
| "company": "MoPub" |
| }, |
| { |
| "date": "2020-04-13", |
| "title": "Using Druid for Network Monitoring and Trust Analytics at Cisco", |
| "name": "TJ Giuli and Abhishek Balaji Radhakrishnan", |
| "link": "https://youtu.be/KXytFBehvXA", |
| "company": "Cisco" |
| }, |
| { |
| "date": "2020-04-13", |
| "title": "Apache Druid Fireside Chat (Ask Us Anything", |
| "name": "Fangjin Yang, Gian Merlino and Vadim Ogievetsky", |
| "link": "https://youtu.be/5JJccj_dSBk", |
| "company": "Imply" |
| }, |
| { |
| "date": "2020-03-03", |
| "title": "How Netflix uses Druid for Real-time Insights to Ensure a High-Quality Experience", |
| "name": "Ben Sykes", |
| "link": "https://netflixtechblog.com/how-netflix-uses-druid-for-real-time-insights-to-ensure-a-high-quality-experience-19e1e8568d06", |
| "company": "Netflix" |
| }, |
| { |
| "date": "2020-01-30", |
| "title": "Introducing Druid 0.17.0", |
| "name": "Gian Merlino", |
| "link": "https://imply.io/post/announcing-druid-0.17.0", |
| "company": "Imply" |
| }, |
| { |
| "date": "2019-12-10", |
| "title": "Druid: Reflections at a Milestone", |
| "name": "Gian Merlino", |
| "link": "https://imply.io/post/reflecting-on-druid", |
| "company": "Imply" |
| }, |
| { |
| "date": "2019-11-21", |
| "title": "How Nielsen Marketing Cloud Uses Druid for Audience and Marketing Performance Analysis", |
| "name": "Itai Yaffe", |
| "link": "https://imply.io/post/nielsen-marketing-audience-analysis", |
| "company": "Nielsen" |
| }, |
| { |
| "date": "2019-10-16", |
| "title": "Druid query view: An elegant SQL interface for a more civilized age", |
| "name": "Margaret Brewster", |
| "link": "https://imply.io/post/druid-console-query-view", |
| "company": "Imply" |
| }, |
| { |
| "date": "2019-09-15", |
| "title": "Data Retention and Deletion in Apache Druid", |
| "name": "Dana Assa and Itai Yaffe", |
| "link": "https://medium.com/nmc-techblog/data-retention-and-deletion-in-apache-druid-74ffd12398a8", |
| "company": "Nielsen" |
| }, |
| { |
| "date": "2019-08-11", |
| "title": "Understanding Spark Streaming with Kafka and Druid", |
| "name": "Daria Litvinov", |
| "link": "https://medium.com/outbrain-engineering/understanding-spark-streaming-with-kafka-and-druid-25b69e28dcb7", |
| "company": "Outbrain" |
| }, |
| { |
| "date": "2019-07-08", |
| "title": "The Zscaler difference - security at cloud scale", |
| "name": "Subramanian Srinivasan and Kevin Fletcher", |
| "link": "https://imply.io/post/druid-at-zscaler-security-log-analytics", |
| "company": "Zscaler" |
| }, |
| { |
| "date": "2019-07-03", |
| "title": "Interactive Analytics at MoPub: Querying Terabytes of Data in Seconds", |
| "name": "Aaron Rolett and Shravana Krishnamurthy", |
| "link": "https://blog.twitter.com/engineering/en_us/topics/infrastructure/2019/interactive-analytics-at-mopub.html", |
| "company": "Twitter" |
| }, |
| { |
| "date": "2019-06-27", |
| "title": "Enrich API Brings Higher Match Rates with Multi-Field Enrichment Capabilities", |
| "name": "Ken Michie", |
| "link": "https://www.fullcontact.com/blog/enrich-api-brings-higher-match-rates-with-multi-field-enrichment-capabilities/", |
| "company": "FullContact" |
| }, |
| { |
| "date": "2019-05-29", |
| "title": "Monitoring at eBay with Druid", |
| "name": "Mohan Garadi", |
| "link": "https://www.ebayinc.com/stories/blogs/tech/monitoring-at-ebay-with-druid/", |
| "company": "ebay" |
| }, |
| { |
| "date": "2019-05-22", |
| "title": "Setting the stage for fast analytics with Druid", |
| "name": "Surekha Saharan and Benjamin Hopp", |
| "link": "https://speakerdeck.com/implydatainc/setting-the-stage-for-fast-analytics-with-druid", |
| "company": "Imply" |
| }, |
| { |
| "date": "2019-03-15", |
| "title": "Data Engineering At Booking.com - a case study", |
| "name": "Andreas Kretz", |
| "link": "https://youtu.be/9GE3yiVo1FM", |
| "company": "Booking.com" |
| }, |
| { |
| "date": "2018-11-14", |
| "title": "How Druid enables analytics at Airbnb", |
| "name": "Pala Muthiah and Jinyang Li", |
| "link": "https://medium.com/airbnb-engineering/druid-airbnb-data-platform-601c312f2a4c", |
| "company": "Airbnb" |
| }, |
| { |
| "date": "2018-09-25", |
| "title": "Data Analytics and Processing at Snap", |
| "name": "Charles Allen", |
| "link": "https://www.slideshare.net/CharlesAllen9/data-analytics-and-processing-at-snap-druid-meetup-la-september-2018", |
| "company": "Snap, Inc." |
| }, |
| { |
| "date": "2018-09-13", |
| "title": "Securing Druid", |
| "name": "Jon Wei", |
| "link": "https://imply.io/post/securing-druid", |
| "company": "Imply" |
| }, |
| { |
| "date": "2018-08-30", |
| "title": "Streaming SQL and Druid", |
| "name": "Arup Malakar", |
| "link": "https://youtu.be/ovZ9iAkQllo", |
| "company": "Lyft" |
| }, |
| { |
| "date": "2018-06-19", |
| "title": "PayPal merchant ecosystem using Apache Spark, Hive, Druid, and HBase", |
| "name": "Deepika Khera & Kasi Natarajan", |
| "link": "https://youtu.be/HJvuU0CQS44", |
| "company": "Paypal" |
| } |
| ] |