Watch this recorded webinar to learn about building real-time analytics for streaming data. Darin Briskman, Imply’s Director of Technology and all around tinkerer, will demonstrate how to use Apache Kafka with Apache Druid, the open-source database for speed, scale, and streaming data...
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Apache Druid is a real-time analytics database used by 1000s of companies like Netflix, Confluent, Salesforce, and Target...
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Come learn about the way that TrueCar uses Druid as the engine to optimize the buying experience through clickstream analytics.
Watch NowAdTech 실시간 광고 분석의 Apache Druid 활용 사례
이 비디오에서는 Apache Druid / Imply를 활용하여 실시간 광고 성과 분석 플랫폼을 구축한 사례, 많은 AdTech 기업들이 Druid / Imply를 선택한 이유, 그리고 실시간 광고...
Watch nowdruid.NEXT
Watch the recording from our druid.NEXT event to see what’s new in Apache Druid 26.0 with technical demos from Apache Druid Committee (PMC) Chair and Imply CTO Gian Merlino along with other Druid committers...
Watch nowBuild Real-Time Analytics for your Kafka Data
Watch this recorded webinar to learn about building real-time analytics for streaming data. Darin Briskman, Imply’s Director of Technology and all around tinkerer, will demonstrate how to use Apache Kafka...
Watch nowApache Druid Explained | Core Concepts
This video provides a technical overview of Apache Druid, a popular real-time analytics database used for sub-second queries on streaming and batch data at scale and under load. The intent of this video is...
Watch nowApache Druid in 5 minutes
Apache Druid is a real-time analytics database used by 1000s of companies like Netflix, Confluent, Salesforce, and Target. But what's the big deal? Why use Druid instead of a data warehouse - like Snowflake,...
Watch nowEmbedding Polaris Visualizations Demo
Set up an embedded visualization solution in under 5 minutes. This short demo highlights the steps needed to build a highly customized application.
Watch nowSpeeding Up Clickstream Data Analytics at Danggeun Market Using Druid
Danggeun market is an online marketplace in Korea focussed on used goods sales in the neighbourhood. This session will detail out how Daangn uses druid to speed up clickstream data analytics. Realtime data...
Watch nowEasy onboard with Polaris
Case study to share my experience how easy is to setup a working Analytics DB by using Imply Polaris. Leverage the batch ingestion APIs using python, using Apache airflow scheduler. How we leveraging Theta...
Watch nowPercentiles at Scale
At Netflix, our engineers often need to see metrics as distributions to get a full picture of how our users are experiencing playback.
Watch nowPowering Clickstream Analytics at TrueCar with Druid
Come learn about the way that TrueCar uses Druid as the engine to optimize the buying experience through clickstream analytics.
Watch nowKeynote: Analytics Meets Applications
How do developers at Netflix, Confluent, and Reddit do more with analytics? They joined a community of like-minded people who bring analytics to applications to power a new generation of operational workflows....
Watch nowDruid SQL for Queries – from an Overview to Tips and Tricks
SQL is a powerful and elegant query language for databases. Druid is increasingly supporting and moving forward with SQL, which is arguably easier to learn and write than the original native (JSON) query language....
Watch nowHow VMware uses Druid for Network & Security Analytics
VMware NSX Intelligence is a distributed analytics platform powered by Druid that can process and visualize network traffic flows, detect anomalous network behaviors, and recommend security policies. We will...
Watch nowKafka Ingestion logs
Apache Druid can handle streaming ingestion jobs at any scale. This occasionally poses challenges. Apache Kafka is a popular distributed event streaming platform, so it’s a natural choice for this presentation....
Watch nowGenerating Time-centric Data for Druid
Sometimes we want to understand how Druid will perform using various types of data, but the actual data may not be available. The developer relations team at Imply has created a data generator program that...
Watch nowLeverage Autonomous Intelligence Driven Decisions Without Using Dashboards
Customer Intelligence facilitates informed decisions to increase business efficiency and success. Out of The Blue™ (OTB) provides SaaS solutions that autonomously and continuously monitor KPIs to create actionable...
Watch nowApache Druid 24.0 New Feature! – Nested JSON
Apache Druid 24.0 has some amazing new capabilities. One of the most exciting ones is the ability to load complex nested JSON structures automatically. In this session we review the motivation for this feature;...
Watch nowUser Activity Analytics in Digital Publishing Domain: Success Story by Indian Express
Indian Express is one of the leading media publishing company based in Mumbai is using Imply for user activity analysis. In this talk, we share how Indian Express migrated their use case from Google Analytics...
Watch nowThe present and future of compaction in Druid
Compaction in the Druid database has been evolving into use cases beyond improving query performance and reducing storage. This talk will first go over what is compaction, current use cases for compaction,...
Watch nowMoving Away from Multi-level Aggregates: Efficiently Scaling Data with Druid
What if I told you moving away from multi-level aggregates could actually speed up your reporting system? In this session, we look at how Druid can be used to retrieve data for reporting quickly and efficiently....
Watch nowAnalyzing Ads Across Medialab’s Global Brands with Druid
In this talk, we will learn more about Medialab's analytics strategy to optimize ad campaigns across several global consumer internet brands using Druid. Juan will highlight the company's journey from Open...
Watch nowLoad, Drop & Kill – The Life of a Segment
In Apache Druid, after ingesting some data and publishing a segment to Deep Storage, it is the Load, Drop rule a Kill process behavior that govern the caching of segments on historicals across multiple tiers....
Watch nowWhy & How We Built An Open-Source Spark Druid Connector – Spark Druid Segment Reader
Spark Druid Segment Reader is a Spark connector that extends Spark DataFrame reader and supports directly reading Druid data from PySpark. By using the DataSource option you can easily define the input path...
Watch nowPushing the Limits of Druid Real-time with Data Sharding
Most Druid applications aim for sub-second analytics queries - but this becomes difficult when dealing with large volumes of real-time data.
Watch nowReal-Time Upserts of Data in Druid
Druid has enabled ThousandEyes to reduce dashboard latency by 10x and provide our customers with a real-time, interactive view of their terabytes of data. In this talk we will learn how the Data Visualization...
Watch nowRealtime Product Observability with Druid
Statsig enables companies to run experiments so that they can understand the impact of the changes they are making to their product, and do in depth analysis so that they can understand how people use their...
Watch nowBuilding Data Pipelines using Druid at Lyft
In this talk, we'll learn more about how Lyft builds data pipelines using Apache Druid, which is useful for several use cases including metrics tracking, model forecasting, and internal tools. We'll also talk...
Watch nowPrinciples of Data Modeling in Apache Druid
Apache Druid is often used to power applications that are fun, fluid, and fast. It’s designed for the last mile, sitting behind a UI where customers, suppliers, and employees are waiting for fast responses...
Watch nowUsing Druid at High Throughput for Fast Queries at Low Cost
ironSource exposed a Druid cluster for its external users, called Real Time Pivot, which runs at a scale of 2-3M events/sec, with tens of TBs added per day, while serving parallel queries within 1-2 seconds....
Watch nowSpeeding up ML Model Training Using Druid
Machine learning models require thousands of data points to train models. This session will look at a number of mechanisms druid offers to speed up model training. The tuple sketch can be used to train models...
Watch nowKeynote: Real time Analytics in Modern SaaS Applications
Real-time analytics has gone from cutting-edge to competitive advantage and is now becoming table stakes. In 8 years and 3 companies of working in the space, Gwen talked to hundreds of companies building real-time...
Watch nowProduction ML Model Quality Monitoring Using Druid
Machine learning and AI have progressed out of the initial technology development phase and into full production. In this new domain, the concept of monitoring has been redefined. Monitoring now fully encompasses...
Watch nowApache Druid 24.0 New Feature! – SQL Based Ingestion
Apache Druid 24.0 has some amazing new capabilities. The Multi-stage Query Architecture (MSQA) that is now a part of the database will enable significant new functionality. In this initial release it enables...
Watch nowIntroducing KUDRAS – Kubernetes Druid Autoscaler for Maximum Resource Utilization and Speed
In this session I would like to talk about the huge amount of data we ingested into Druid (raw data is 9 Terra per day) by using EMR, all orchestrated by Airflow. While the data grew we started experiencing...
Watch nowAtlassian: Delivering insights to Confluence Users at Enterprise Scale
Druid is a powerful tool that has paved the way for a whole new wave of data-focused tech. In the Confluence Analytics team, we ingest millions of events every day and use this tool to power a plethora of features...
Watch nowNew Druid Challenges and Solutions in Pinterest
Pinterest has been using Druid with large ingestion scales and low query latency for a few years. In this talk, we will share recent optimizations we made on querying skewed data, how we deal with large scale...
Watch nowLow Latency Real Time Ads Pacing Queries
Advertising backend systems need low latency for the efficient delivery and availability of budget data to the ad serving infrastructure. For the reddit team, we helped automate user behavior analysis to serve...
Watch nowKeynote: Building Next-Gen Observability at Confluent
In this Q&A, Matt Armstrong, Head of Engineering - Observability & Data Platform at Confluent will discuss the use cases and architecture for Confluent's observability platform. Confluent leverages both Druid...
Watch nowHow is Druid so Fast?
A look at how Apache Druid is able to achieve high concurrency subsecond queries at scale.
Watch nowApache Druid’s Fit in the Modern Data Stack
Apache Druid is a real-time analytics database for analytics applications. It’s used by 1000s of companies like Netflix, Confluent, Target, and Salesforce. In a crowded database market, it can be hard to...
Watch nowHandling row level updates in druid using a kafka lookup
This video shows how to configure and populate a kafka lookup and then use it in a query to handle row level updates in druid
Watch nowModern Analytics Applications in the Financial Industry
Join Eric Tschetter, Field CTO of Imply and co-creator of Apache Druid, Ravi Maurya and Shubham Gupta from Paytm in this inspiring virtual event
Watch nowThe New Database Battle: Apache Druid vs. ClickHouse
They both say they’re fast; they both say they scale. Should you flip a coin or are there real technical differences that matter? Watch this webinar and get the facts that lay out the differences.
Watch nowHow-to Half-hour: Using Multi-value Dimensions in Apache Druid
If you’ve tried, you probably did tons of JOIN operations to build an array. Did you know that with multi-value dimensions you can filter and group complex data quickly and easily?
Watch nowKeynote – Building Modern Analytics Applications with Apache Druid
Fangjin Yang, Co-Founder and Chief Executive Officer of Imply, presents the opening keynote at the Druid Summit 2021 virtual conference.
Watch nowTechnical deep dive into how Outbrain scales its real-time analytics
Because Outbrain processes billions of impressions and events a day, they risk running into scaling problems.
Watch nowImply x Kafka: Capture, interact and scale streaming data
Imply and Kafka is the perfect architecture to capture and surface streaming data through interactive queries and unlimited scale
Watch nowConfluent Cloud 연동하여 Imply로 실시간 데이터 분석 및 시각화
라이브 데모: 대화형 쿼리 및 제한없는 확장을 통해 스트리밍 데이터를 캡쳐하고 보여주는 아키텍쳐를 구축하는 방법
Watch nowMaking Real-Time Data a Reality for your Business
Technaura takes you through an hour of practical Real-time, data-driven outcomes.
Watch nowApache Druid Engine Roadmap
如果你还在每天等待数据刷新，是时候试试Apache Druid 亚秒级数据库了。 该开源数据库在Twitter、Pinterest和Snapchat广泛部署。此次研讨会中， Imply的产品经理Will...
Watch nowComparing drill-down workflows between Tableau & Snowflake with Imply
In this video, Jad Naous demonstrates drill-down workflows between Tableau & Snowflake with Imply.
Watch nowHow Spideo turbo-charged data analytics by using Imply
In this video, Spideo, a humanized recommendation provider, shares with us its data analytics journey.
Watch nowPivot 2.0 – The Next Gen Visualization Tool
In this webinar, will walk you through the exciting new features that are coming soon to Pivot.
Watch nowIntroducing… Druid’s Components
In this talk, we look at the three families of components that create “Apache Druid.”
Watch now积跬步，至千里——详解运用流数据的商业价值
商业用户越来越意识到企业活动产生的数据能够及时帮助他们洞见日常运营对自身现有商业模式的影响以及是否有利于企业的长远决策。
Watch nowAnalyser Des Flux De Donnees Massifs Avec Imply
NOVAGEN présentera un cas avec IMPLY, inspiré de ses projets menés dans le secteur de la grande distribution, qui a su répondre à ces nouveaux enjeux :
Watch nowUsing Imply to prevent fraud
Learn a new methodology for anomaly detection and analysis that can be applied to everything from fraud detection to factory accident prevention.
Watch nowInside Apache Druid’s storage and query engine
We’ll cover how Druid stores data, what kinds of compression it uses, how it indexes data, how the storage engine is linked with the query processing engine.
Watch nowFirst look: Imply CrossTab (beta)
In this short video, Imply Chief Product Officer Vadim Ogievetsky demonstrates a cool new beta feature, Imply CrossTab.
Watch nowImply CrossTab: PivotTables to infinity and beyond
In this webinar we will introduce Imply CrossTab, a new visualization that makes the pivot table user experience feel instantaneous.
Watch nowElasticsearch: pros and cons for real-time analytics
In this video, solution architect Itai Yaffe shares what Elasticsearch provides for analytic use cases compared to Imply.
Watch nowWhere do Imply and Elasticsearch fit in my big data stack?
Itai Yaffe shares how Imply and Elasticsearch fit in a modern architecture for big data.
Watch nowHow Imply fulfills the requirements of real-time analytics
Data wizard Itai Yaffe explains how Imply's platform fills the requirements of general-purpose operational analytics.
Watch nowNear term Apache Druid roadmap for 2021
Gian Merlino, Apache Druid PMC Chair, lays out the near team Druid roadmap.
Watch nowWhat’s new in Apache Druid?
Looking for a recap of the key improvements to Apache Druid in its most most recent releases? Here’s the video for you.
Watch now5 minute explanation of Imply’s advantages for self service analytics
We describe the Imply full-stack, multi-cloud data platform, and Itai breaks down the unique combination of features Imply brings to self-service analytics.
Watch nowThe Superstars of Apache Druid meetup
The Superstars of Apache Druid meetup was recorded live on 1-21-2021. Talks from Dan Prince from Target, Gian Merlino, and Vadim Ogievetsky
Watch nowComparing Elasticsearch and Imply for operational analytics
If you’re considering using it for interactive analytics, be advised that it’s quite common to see companies struggling with Elastic-based analytic solutions.
Watch now3 different approaches to multi-tenant applications
The three main challenges with multi-tenant applications are cost, performance, and data management.
Watch nowHow Apache Druid ensures quality of service
Gian Merlino covers Druid’s use of tiers, lanes and priorities to address QoS and deliver consistent performance as you scale demand.
Watch nowBuilding interactive data applications for event streams w/Confluent
Data apps let business users explore and investigate all of a company's event data and come to insights that impact day-to-day and long-range decision making.
Watch nowOutbrain’s real-time analytics architecture
Outbrain’s real-time analytics architecture consists of modern big data technologies like Kafka, Spark, Druid and Imply Pivot for query and visualization.
Watch nowLyft’s modern data architecture feat. Apache Druid, Kafka and Flink
Take a look at Lyft’s modern data architecture. They have an app implemented in Flink that reads real-time event data from Kinesis and transforms the data.
Watch nowTechnical reasons why Lyft chose Apache Druid for real time analytics
In this video, Sharanya Santhanam from Lyft explains the key technical reasons why they chose Druid as the engine for their real-time data pipeline.
Watch nowLyft’s Apache Druid uses cases
Lyft uses Apache Druid for three core use cases: geo-spatial data lookups for rideshare customer service, analytics on AWS cloud infrastructure spend.
Watch nowAchieve the event-driven Nirvana with Apache Druid
We will explain how Apache Druid enables self-service BI on event data and allows business users to ask their own questions leading to real-time insights.
Watch nowApache Druid and database evolution
A look at how Druid builds on the long history of database engines, and what that means for technologists and decision-makers.
Watch nowApache Druid data optimisations
A telling of the tale of how Druid can optimize data as it is ingested, turning it into a format perfect for interactive, real-time analytics.
Watch nowVirtual Druid Summit 2020 highlights
Catch all of the amazing highlights from our free Virtual Druid Summit. We had four amazing events that took place between April 10 to November 20, 2020.
Watch nowA demo of how Imply powers real-time data applications
Learn more about how Imply powers real-time data applications. In this demonstration video, Sales Engineer Vasilis Vagias walks you through the product.
Watch nowScaling Apache Druid as a multi-tenant platform
In this talk I will present: Our data model in Druid, based on UNION of several different types of events.
Watch nowOutbrain: Moving real-time analytics to the next level
In this talk I will present: Our data model in Druid, based on UNION of several different types of events.
Watch nowEnabling real-time querying using Druid & Flink @ Lyft
In this talk, we’ll learn more about how Apache Druid powers alerting against real-time data at Lyft.
Watch nowInnowatts: Analyzing electric meters using Druid
Learn how they use Druid to power visualizations that users can interactively explore, shortening the time it takes to diagnose data, and off-loading Spark.
Watch nowBuilding a real-time eventing engine at FullContact
In this talk, Jeremy Plichta will outline FullContact’s journey with Apache Kafka and Druid
Watch nowImply Cloud on AWS demonstration
Want to see how to set up, use and manage Imply Cloud for real-time self-service analytics at scale?
Watch nowApache Druid 101
This talk provides an introduction to Apache Druid including: Druid's core architecture and its advantages.
Watch nowWhat is a data application?
Data applications are visually-oriented and designed for non-analysts to investigate and explore large, fast-moving data sets.
Watch nowThe 5 things data applications need
What do data applications need? Imply CTO Gian Merlino boils it down to 5 key things.
Watch nowHow Apache Druid addresses the 5 requirements of data applications
Data applications are visually-oriented and designed for non-analysts to investigate and explore large, fast-moving data sets.
Watch nowSuperAwesome Returns for a SuperAwesome Apache Druid Meetup
In this talk, we walk through how we run Druid on spot instances.
Watch nowThree reasons why Target built a custom enterprise analytics platform
Target explains why they built a custom analytics platform, focusing on self-service development, discovery /collaboration of data, and to ensure scalability.
Watch nowTarget explains unions in Apache Druid
In this short video, Jeremy Woelfel of Target explains how unions allow them to blend their data.
Watch nowKey Apache Druid features Target utilizes
Jeremy Woelfel of Target explains how they ingest their data, the impact of cardinality, metrics collection, Thetasketch approximations, and more!
Watch nowApacheCon @Home Thursday Keynote: Gian Merlino, Imply
Gian Merlino discuss why you can never find that single perfect system and how to think about & evaluate data on a temperature-based spectrum.
Watch nowA explainer about Druid rollup, cardinality and segments from Netflix
In this short video, Ben Sykes of Netflix explains Druid roll-up, the impact of high cardinality, and segment sizing.
Watch nowWhat’s inside Netflix’s metrics pipeline & Apache Druid cluster?
Ben Sykes discusses how Netflix created its metrics pipeline to ensure a high-quality streaming experience & how they structure their Apache Druid cluster.
Watch nowBuilding Data Applications with Apache Druid
One of the most popular use cases for Apache Druid is building data applications.
Watch nowGameAnalytics: Building a Real-Time Gaming Analytics Service w/ Druid
In this talk, you will learn how we managed to migrate our legacy backend system from using an in-house built streaming analytics service to Apache Druid.
Watch nowZeotap: Data Modeling in Druid for Non temporal and Nested Data
Druid has been the production workhorse for the past 2+ years at Zeotap powering the core Audience planning across our Connect and Targeting products.
Watch now