The Imply Blog

We write about our product, technology, and company

Virtual Druid Summit Returns with Talks from Pinterest, Splunk, GameAnalytics, Nielsen, and Zeotap

Jelena Zanko · September 18, 2020

Though you might have heard that Virtual Druid Summit was returning, did you guess that it would be so soon? We’re stoked, too! The third installment of Virtual Druid Summit will be taking place on October 7, 2020.

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Real-Time data and analytics for fantasy sports

Pradip Thoke, Dream11 · September 17, 2020

Dream11, India's biggest fantasy sports platform, serves over 2.5 million concurrent users and handles 40 million requests per minute. Learn how Imply helped them achieve operational data excellence through a new in-house analytics platform.

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Extend your cloud data warehouse to power modern, interactive data applications

Rick Bilodeau · September 16, 2020

Snowflake's IPO today is a testament to the importance of data analytics and the cloud in business today. This post describes how Imply complements cloud data warehouses for a growing set of workloads called interactive data applications, which require sub-second query response at high user concurrency.

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Imply Cloud Free Tier now available!

Rick Bilodeau · September 15, 2020

Today I am happy to tell you that we have just announced immediate availability of a free tier for the Imply Cloud service, so you can try out the power of the Imply platform easily and free-of-charge.

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Community Spotlight: Mindhouse Achieves Monitoring Nirvana with Apache Druid

Matt Sarrel · September 10, 2020

We recently discussed Mindhouse’s use of Apache Druid for clickstream data analysis and user behavior funnel analysis with Ankur Gupta, the company’s engineering technical lead. Ankur’s team relies on Druid to “segment users and understand how they are using our app”, and finds that “it’s especially helpful when we launch a new feature because we can understand the acceptance of the feature based on current user activity”.

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Combating fraud at Ibotta with Imply

Jaylyn Stoesz, Ibotta · Laura Reamey, Ibotta · September 9, 2020

For years, fraud was primarily a game of strategy. Fraudsters sought to disguise their true intentions and fraud prevention was an art of detection. Today, fraud is still a game of wits but it has also evolved into a game of speed and volume. The advancement of technology and explosion of e-commerce has had a compounding effect.

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Apache Druid hits 10,000 Github star milestone

Matt Sarrel · September 9, 2020

We’ve always believed that community growth and collaboration is critical to the success of Apache Druid. For this reason, we’re excited to announce that last week, the Druid Github repository passed 10,000 stars!

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How Adikteev helps customers succeed using self-service analytics

Margot Miller, Adikteev · Loic Anton, Adikteev · August 20, 2020

Adikteev is the leading mobile app re-engagement platform for performance-driven marketers, and is consistently ranked in the top 5 of the Appsflyer Performance Index. This post discusses how we use Imply to react in real-time to live data from diverse sources to gain actionable insights, thereby improving customer mobile app engagement and making our customer success managers more productive.

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Join Target, Twitch, Netflix and TrafficGuard on the Sep 2 Edition of Virtual Druid Summit!

Jelena Zanko · August 19, 2020

Because we care deeply about the health of the community while continuing to deliver the most interesting Apache Druid stories, we’re hosting the second edition of Virtual Druid Summit II on September 2, 2020.

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Introducing Apache Druid 0.19

Will Xu · July 16, 2020

The Apache Druid community released Druid 0.19 on July 21st, 2020. This release contains over 200 new features, performance enhancements, bug fixes, and major documentation improvements from 47 contributors.

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Hot analytics and the data warehouse deficit

Matt Sarrel · Peter Kacandes · July 15, 2020

One of the most important considerations when selecting an analytics platform is its suitability to conduct the required analyses over specific types of data within a given performance threshold. A helpful way to think about this is to utilize the concept of temperature-tiered analytics to align analytics needs with data architectures.

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Introducing Imply 3.4

Jad Naous · July 13, 2020

We’re excited to announce the release of Imply 3.4 with Apache Druid 0.19 at its core. This release includes new capabilities in Druid and Pivot that bring the stack closer to standard BI capabilities along with dozens of bug fixes and enhancements.

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Price-performance benchmark Apache Druid and Google BigQuery

Rick Bilodeau · June 25, 2020

A new benchmark test indicates that Apache Druid, the engine that drives the Imply real-time data platform, delivers 3 times the speed and 12 times the price-performance of Google BigQuery.

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The Secret to Apache Druid Success

Rob Meyer · June 10, 2020

There is no doubt that Apache Druid is a success, or that the benefits of implementing Druid can be huge. It is the leading real-time analytics database on the market. Thousands of companies use it to use it to equip their employees and customers with self-service analytics to make better, faster decisions.

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Tutorial: Add BGP Analytics to your Imply netflow analysis

Eric Graham · Paolo Lucente, NTT · June 8, 2020

Imply is a real-time data platform for self-service analytics. It is very well suited for high performance analytics against event-driven data. One of the common use cases is to store, analyze, and visualize different types of networking data (NetFlow v5/v9, sFlow, IPFIX, etc.).

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Introduction to JOINs in Apache Druid

Gian Merlino · June 4, 2020

In Apache Druid 0.18/Imply 3.3, we added support for SQL Joins in Druid. This capability, which has long been demanded from Druid by the community, opens the door to a large number of possibilities in the future. In this blog I want to highlight some of the motivations behind us undertaking the effort and give you, the reader, an understanding of how it can be useful and where we’re going with it.

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Apache Druid Best Practices - Determining Worker Capacity (slots) for Automatic Compaction

Venkatraman Poornalingam · May 22, 2020

In Apache Druid, Compaction basically helps with managing the segments for a given datasource. Using compaction, we can either merge smaller segments or split large segments to optimize segment size. One of the first options to consider would be to determine, if the segments could be generated optimally. If that isn’t possible, compaction would be required.

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Introducing Apache Druid 0.18.0

Will Xu · May 21, 2020

The Apache Druid community released Druid 0.18 on April 20th, 2020. This release contains over 200 new features, performance enhancements, bug fixes, and major documentation improvements from 42 contributors.

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Continuing the Virtual Druid Summit Conversation with Athena Health

Karthik Urs, Athena Health · May 11, 2020

When an engaged technical audience asks great questions, it’s easy to run out of time during Q&A. And that’s exactly what happened at Virtual Druid Summit! Because our speakers weren’t able to address all of your questions during the live sessions, we’re following up with the answers you deserve in a series of blog posts.

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When a Data Warehouse Can’t Keep it Real-Time

Rick Bilodeau · May 4, 2020

This short post describes how Druid compares against enterprise data warehouses. Druid is not a data warehouse. It's a real-time database for user-facing analytics application needing sub-second query response at high concurrency.

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Continuing the Virtual Druid Summit Conversation: Twitter has Answers

Swapnesh Gandhi, Twitter · May 1, 2020

Thanks again to everyone who attended Virtual Druid Summit, and for being so engaged – as we previously mentioned, our speakers received more than 150 questions across their collective sessions! Unfortunately, there wasn’t enough time to answer all of your very good questions during the live sessions. In an effort to bring you some closure, we’ve invited our esteemed speakers to address the remaining questions in a series of blog posts.

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What Went Down at the Virtual Druid Summit

Rachel Pedreschi · April 24, 2020

I want first to thank everyone involved with making our first, albeit a tad non-standard, Druid Summit a smashing success. We, and the hundreds of folks who had purchased tickets, were extremely disappointed to postpone our first physical Druid Summit to November, but we were fortunate to have 10 great speakers agree to do their presentations virtually.

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Announcing Imply 3.3

Vadim Ogievetsky · April 15, 2020

We are excited to announce the general availability of Imply 3.3, which greatly expands the expressivity of SQL by adding the ability to do JOINs and interact with lookups in novel ways. This release includes over 200 new features, performance enhancements, bug fixes, and major documentation improvements.

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Behold the void: Measuring the performance impact of numeric column NULL checks in Apache Druid

Clint Wylie · April 6, 2020

In this post, I am going to talk a bit about Apache Druid and a recently documented configuration option that enables true NULL values to be stored and queried for better SQL compatibility: druid.generic.useDefaultValueForNull=false, and in the process do a deep dive into how it relates to a small sliver of the query processing system as we explore the performance of this feature.

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Announcing Virtual Druid Summit - April 15, 2020

Rick Bilodeau · March 24, 2020

I am happy to tell you that 10 days after we officially postponed Druid Summit, we have now launched Virtual Druid Summit, which will take place as a series of online talks on April 15. Each talk will be a spicy 30 minutes of real-world information, followed by Q/A. There are 5 talks from Druid practitioners from a variety of industries and spanning 3 continents. The summit will open with a Apache Druid Roadmap and Vision talk from Apache Druid PMC Chair Gian Merlino, and will close with a 2-way voice-interactive “ask us anything” session featuring Druid authors and contributors.

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Imply Releases A Reference Architecture for Apache Druid on Microsoft Azure

Matt Sarrel · March 17, 2020

Tijo Thomas, a Solutions Architect at Imply, recently wrote a reference architecture for Apache Druid on Microsoft Azure that includes some best practices for running on services such as Azure VM, Azure Blob Storage, Azure Database Service and HDInsight.

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A Reference Architecture for Real-Time IoT Analytics feat. Apache Druid

Eric Graham · February 28, 2020

Analyzing the potential petabytes or more of data from all these devices goes way beyond existing data warehouses or data lakes. Fortunately companies have already implemented IoT analytics using Imply, the real-time intelligence platform built on Apache Druid, the leading open source real-time time analytics database.

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Why I joined Imply

Jad Naous · February 19, 2020

I’ve been leading engineering and product at Imply for 5 months now, and every day is more exciting than the one before. Just before Imply, I was a Partner at Andreessen Horowitz, directly involved in the investments in tens of companies and on the board of many. Many wonder: "having seen hundreds of companies at Andreessen Horowitz, why did I choose Imply?” The truth is it would have been a mistake not to.

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Announcing Imply 3.2

Vadim Ogievetsky · January 30, 2020

We are delighted to announce that Imply 3.2 is now available! Imply 3.2 is based on Apache Druid 0.17 (Druid’s first Apache top level project release) and adds new cloud management, alerting, reporting, and data loading features.

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Introducing Druid 0.17.0

Gian Merlino · January 30, 2020

Earlier this week, the Apache Druid community released Druid 0.17.0. This is the project’s first release since graduating from the Apache Incubator, and it therefore represents an important milestone.

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Apache Druid on Google Cloud Platform (GCP) Reference Architecture

Matt Sarrel · January 29, 2020

Muthu Lalapet, a Solutions Architect at Imply, recently wrote a reference architecture for Apache Druid on Google Cloud Platform (GCP) that includes some best practices for leveraging GCP services such as Compute Engine, Cloud Storage and Cloud SQL. The document describes example cluster architectures and their accompanying machine types and configurations. As such, it’s a helpful resource for planning and implementing Druid on GCP.

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Why Vertica Customers Adopt Apache Druid for Real-Time Analytics

Rob Meyer · January 13, 2020

If you are a Vertica customer, you probably already know this. Vertica is not built for real-time operational analytics at scale. If you do not know Vertica very well, you might be surprised. This statement may seem controversial. It’s not. Nearly ¼ of Imply customers were existing Vertica customers who purchased Imply, a commercially supported version of Apache Druid, because they were trying to implement operational analytics and hit limitations with Vertica. Other Vertica customers also use open source Druid and self-support.

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Apache Druid and Imply Best Practices for GDPR and CCPA Compliance

Rob Meyer · January 8, 2020

If you are using Apache Druid to analyze customer-oriented data you are probably familiar with the General Data Privacy Regulation (GDPR), which went into effect May 25, 2018. However, you may be less familiar with a new law, the California Consumer Privacy Act (CCPA), which went into effect January 1, 2020 and is likely become a *de facto* standard in the US.

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Druid: Reflections at a Milestone

Gian Merlino · December 10, 2019

Today, Imply announced a new round of growth funding raised from Andreessen Horowitz and Geodesic Capital. First I want to thank these firms for their support and for sharing our vision as we continue to grow. Thank you, too, to all of our customers for joining us on this journey. A milestone like this is a good time to reflect on the past and the future.

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Imply Raises $30M in Series B funding at $350M Valuation

Fangjin Yang · December 10, 2019

I’m excited to announce that Imply has raised a $30M Series B funding round led by Andreessen Horowitz, with participation from Geodesic Capital and Khosla Ventures. We are excited to partner again with A16Z as the lead investor to continue to build out the company, and we look forward to working closely with Geodesic Capital towards international expansion.

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How Nielsen Marketing Cloud Uses Druid for Audience and Marketing Performance Analysis

Itai Yaffe · November 21, 2019

Nielsen Marketing Cloud uses Druid to profile the various audiences that marketers and publishers would like to target on digital media, activate via various ad networks, and then gain insights on that activation after the fact.

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Druid query view: An elegant SQL interface for a more civilized age

Margaret Brewster · October 16, 2019

In the 0.16 console, we have added a new layer of SQL awareness to the query view to help move the view away from its roots as a text-only interface, to a point and click one.

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Announcing Imply 3.1

Vadim Ogievetsky · September 26, 2019

We are delighted to announce that Imply 3.1 is now available! Imply 3.1 is based on Apache Druid 0.16 and contains many improvements.

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Introducing Apache Druid 0.16.0

Gian Merlino · September 26, 2019

Like every Druid release, this one has a huge amount and variety of fixes and new functionality. This particular one include over 350 new features, performance enhancements, bug fixes, and major documentation improvements from 50 contributors.

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Clickstream Funnel Analysis with Apache Druid

Mike McLaughlin · September 11, 2019

Apache Druid is commonly used for clickstream funnel analysis, and in this blog post we’ll deep dive into how you can collect and analyze funnel data. While there are applications designed for clickstream analysis, such as Google Analytics and Adobe SiteCatalyst (previously Omniture), Druid is ideal when you have significant scale.

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Apache Druid helps Zeotap Master Multi-Channel Attribution at Scale

Chaitanya Bendre, Zeotap · August 22, 2019

Below is a transcript of a short interview we conducted with Chaitanya Bendre, Lead Data Engineer at Zeotap, where we discussed there use of Druid to help address the difficult problem of identity resolution and multi-channel attribution.

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Blueshift: Scaling real-time campaign analytics with Apache Druid

Anuraj Pandey, Blueshift · August 8, 2019

Blueshift is an AI-powered customer data activation platform enabling CRM and product marketers to intelligently manage their audiences and orchestrate large-scale personalized messaging campaigns at scale. Blueshift offers real-time campaign analytics as a core capability in the platform. Campaign analytics break down engagement metrics like impressions, clicks, conversions etc by channel, trigger, experiment etc. Currently two billion+ user interactions are tracked on a monthly basis.

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Independent Performance Benchmark: Apache Druid versus Presto and Apache Hive

Rick Bilodeau · July 17, 2019

A recent paper by independent researchers at the University of Minho in Portugal compared the performance of Apache Druid to well-known SQL-on-Hadoop technologies Hive and Presto. In the tests, Druid outperformed Presto from 10X to 59X (90% to 98% speed improvement) and Hive by over 100X.

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Announcing Imply 3.0

Vadim Ogievetsky · July 15, 2019

We are delighted to announce that Imply 3.0 is now available! It contains many usability features such as a visual data loader, on-premises cluster and alerts functionality.

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Hadoop Indexing for Apache Druid at Scale - Configuration Best Practices

Rommel Garcia · July 12, 2019

When Hadoop is pushing data into Druid, Hadoop indexer performance is key and becomes challenging at scale. There are a quite a few things to consider when running large scale Hadoop indexing.

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Druid @ Zscaler - A Retrospective

Subramanian Srinivasan, Zscaler · Kevin Fletcher, Zscaler · July 8, 2019

This document outlines the journey Zscaler made in building Zscaler Private Access (ZPA) and focuses on the analytics component of our solution. We will discuss some of our early requirements, why we picked certain technologies, such as Druid/Imply, and how we run things today.

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Interactive Analytics at MoPub (Twitter): Using Druid and Imply to Query Terabytes of Data in Seconds

Rick Bilodeau · July 5, 2019

MoPub, a Twitter company, has just launched a new solution called MoPub Analytics based on Apache Druid and using Imply Pivot as the drag-and-drop UI. The solution allows users to determine the root cause of new data trends by interactively analyzing the data across many different time slices, dimensions, and metrics.

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Introducing Apache Druid 0.15.0

Gian Merlino · June 27, 2019

Today, the Apache Druid community released Druid 0.15.0-incubating. Druid is known as an extremely high-performance database and much of the early design work has been focused on providing speed at scale. Lately we have made a pivot towards those “ease of” factors that help users get productive with Druid quickly.

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Results of the first Apache Druid (incubating) community survey

Gian Merlino · June 25, 2019

We recently conducted our first Druid community survey. Every so often we’ll be asking our community a short set of questions to understand how they use Druid, and how they would like to see it improved.

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Clickstream Analysis - An Open Source Architecture

Mike McLaughlin · Peter Marshall · June 12, 2019

A triad of open source projects - Divolte, Apache Kafka and Apache Druid - can power real-time collection, streaming and interactive visualisation of clickstreams, so you can investigate and explore what’s happening on your digital channels as easily as looking out of your office window.

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Apache Druid vs. Time-Series Databases

Rick Bilodeau · June 11, 2019

Although Druid draws ideas from a number of TSDB concepts, it is designed for a wider range of analytic use cases than those for which a TSDB is usually employed.

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Tutorial: Using Apache Druid and Imply With Google Cloud Dataproc For Hadoop Indexing

Rommel Garcia · June 6, 2019

To help you get to know GCP and Druid, the tutorial below will walk you through how to install and configure Druid to work with Dataproc (GCP’s managed Hadoop offering) for Hadoop Indexing. Then it will show you how to ingest and query data as well.

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Tutorial: An End-to-end Streaming Analytics Stack for Juniper Streaming Telemetry

Eric Graham · May 23, 2019

In this tutorial, we will step through how to set up Imply, Kafka, and Open-NTI to build an end-to-end streaming analytics stack that can handle Juniper Native streaming telemetry data.

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Tutorial: An End-to-end Streaming Analytics Stack for syslog Data

Eric Graham · April 18, 2019

In this tutorial, we will step through how to set up Imply, Kafka, and syslog-ng kafka to build an end-to-end streaming analytics stack that can handle many different forms of log data.

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Swimming in the Data River or: How We Got to Streaming Analytics

Rachel Pedreschi · April 16, 2019

Businesses need to understand how their metrics change across many facets of their operations, and this is the core idea behind data analytics.

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Announcing Imply 2.9

Vadim Ogievetsky · April 10, 2019

Imply 2.9 is based off of the just announced Druid 0.14. Druid 0.14 contains many new features, improvements, and bug fixes. This blog post will focus on the new Imply components and features not available in Druid 0.14.

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Announcing Druid 0.14.0

Gian Merlino · April 9, 2019

Today the Apache Druid community released Druid 0.14.0, our second release under the Apache umbrella and the first major release of 2019. I thought I'd take this opportunity to talk about what's new in this release and what's coming in the future.

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How WalkMe uses Druid and Imply Cloud to Analyze Clickstreams and User Behavior

Yotam Spenser, WalkMe · April 3, 2019

WalkMe uses Imply Cloud to monitor behavioral analytics for its leading Digital Adoption Platform.

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Tutorial: An End-to-end Streaming Analytics Stack for Network Telemetry Data

Eric Graham · March 26, 2019

In this tutorial, we will step through how to set up Imply, Kafka, and pmacct to build an end-to-end streaming analytics stack that can handle many different forms of networking data.

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How to analyze AWS VPC logs with Imply

Eric Graham · March 14, 2019

Have you ever wanted more visibility in your AWS network traffic? This how-to blog covers how to analyze VPC flow logs with Imply.

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Apache Cassandra vs. Apache Druid

Rachel Pedreschi · March 6, 2019

If you are reading this because you are considering whether to use Apache Cassandra/DSE/ScyllaDB or Apache Druid/Imply, then you can just stop right now.

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Using Druid to fight ad fraud

Raigon Jolly, TrafficGuard · February 27, 2019

TrafficGuard helps some of the world’s biggest digital advertisers and agencies protect their ad spend from fraud. Our clients need access to reliable reporting in real-time to allow them to optimise their ad campaigns with current insights.

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Why GameAnalytics migrated to Apache Druid, and then to Imply

Ramón Lastres Guerrero, GameAnalytics · February 14, 2019

At GameAnalytics, our user base has grown several times over in the past 12 months, and this growth has promoted us to rethink our user experience analytics system.

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Kappa architecture at NTT Com: Building a streaming analytics stack with Druid and Kafka

Paolo Lucente, NTT · January 8, 2019

One of the key activities at the heart of any internet backbone is flow analytics, which enables visibility into global traffic for many technical, economical, and security use cases. By providing real-time traffic visibility and rapid explanation capabilities for this data, we unlock tremendous business value for the whole organization.

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Announcing Imply 2.8

Vadim Ogievetsky · December 18, 2018

Imply 2.8 comes with the first Apache release of Druid and a host of features aimed at performance improvements and ease of use.

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Imply lookups for enhanced network flow visibility

Eric Graham · November 26, 2018

Within Druid there are multiple ways to enhance visibility for existing network flow records. This how-to blog covers one way to do this using Druid lookup tables.

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Modernizing Rubicon Project’s Analytics Stack for Programmatic Advertising

Ken Lin · October 22, 2018

Rubicon Project, one of the world’s largest digital advertising exchanges, has modernized their analytics stack with Druid and Imply.

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Securing Druid

Jon Wei · September 13, 2018

Security is a critical requirement in every deployment of a system that holds and processes data. In this blog post, we will discuss how we secured Apache Druid, and validated our implementation.

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Announcing Imply 2.7

Vadim Ogievetsky · September 11, 2018

In Imply 2.7, we have added a selection of new visualizations and a new Explain feature that allows you to discover the contributing factors to any slice of data. We are also introducing advanced access control features, and have made several improvements to loading and managing data.

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Who is knocking on our door? Analyzing AWS Netflows

Vadim Ogievetsky · June 27, 2018

We ingested our internal AWS VPC netflows into Imply and found something surprising.

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Announcing Imply 2.6

Vadim Ogievetsky · June 19, 2018

Imply 2.6 introduces time compares, data export, advanced aggregation measures, and more!

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Announcing Imply 2.5

Vadim Ogievetsky · March 23, 2018

Imply 2.5 comes with an improved streaming data loader, a sunburst visualization, many dashboard improvements, and more.

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March 2018 Druid Meetup - eBay Monitoring Platform

Gian Merlino · March 22, 2018

March 2018 Druid Bay Area Meetup - eBay Monitoring Platform, links to slides

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Imply Raises Series A funding

Fangjin Yang · March 13, 2018

I'm excited to announce that Imply has raised a $13.3M Series A, led by Andreessen Horowitz, and joined by our seed investor, Khosla Ventures.

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Announcing Imply Cloud: Managed Service for AWS

Vadim Ogievetsky · March 13, 2018

Today, we are excited to announce that Imply Cloud, a fully managed service for AWS, is now generally available.

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Announcing Imply 2.4

Vadim Ogievetsky · December 19, 2017

Imply 2.4 comes with a preview of a dataset manager, new features, improvements, bug fixes, and more!

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End-to-end Security in Druid

Jon Wei · December 18, 2017

It is now possible to deploy a druid cluster in a secure setting.

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November 2017 Druid Bay Area Meetup - MZ, Slack, Druid Roadmap

Gian Merlino · November 29, 2017

November 2017 Druid Bay Area Meetup video, with talks from MZ and Slack, and a Druid roadmap update from Imply

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Announcing Imply 2.3: An Integrated Platform

Vadim Ogievetsky · August 23, 2017

Imply 2.3 comes with brand new apps, new features, improvements, bug fixes, and more!

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Announcing Imply 2.2: Pivot Features Galore

Vadim Ogievetsky · May 16, 2017

We're excited to announce Imply 2.2, with tons of new features for Pivot.

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Announcing Imply 2.1

Vadim Ogievetsky · April 19, 2017

We are extremely excited to announce Imply 2.1, a feature-packed release, available now for download. Native SQL comes to Druid and dashboarding is now possible in Pivot.

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Druid February Meetup Slides

Fangjin Yang · February 23, 2017

Our last Druid meetup had great talks about how Druid is used at Branch, the ongoing work around better integrating Druid with the Hadoop ecosystem, and our roadmap plans.

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Druid December Meetup Videos

Fangjin Yang · December 21, 2016

Our last Druid meetup at Sift Science had 3 great talks about use cases with Druid & Imply, and the upcoming Druid roadmap.

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Compressing Longs in Druid

David Li · December 7, 2016

With the Druid 0.9.2 release, Druid has added additional column compression methods for longs to significantly improve query performance in certain use cases. In this blog post, we’ll highlight how these various compression methods impact data storage size and query performance.

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Pivot 0.10.27 Release

Vadim Ogievetsky · December 1, 2016

It’s been some time since our last release of Pivot. Today, after much hard work, we are excited to announce version 0.10.27, which represents a significant step towards a more holistic data exploration experience.

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Druid 0.9.2 Release

Gian Merlino · December 1, 2016

The Druid community is pleased to announce our next major release, 0.9.2. We’ve added hundreds of performance improvements, stability improvements, and bug fixes.

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Announcing Imply 2.0

Fangjin Yang · December 1, 2016

We are extremely excited to announce Imply 2.0, our largest release ever, available now for download. This release contains significant updates to both Druid and Pivot.

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Farewell Lambda Architectures: Exactly-Once Streaming Ingestion in Druid

David Lim · July 5, 2016

Today, many companies are turning to streaming solutions which are enabling them to understand and make business decisions from their data immediately, resulting in an operational agility that was unthinkable only a few years ago. The new Kafka indexing service is an exciting milestone in the maturity of Druid's ingestion technology, giving users a way to stream data into Druid with exactly-once correctness.

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Announcing Imply 1.3.0

Fangjin Yang · June 29, 2016

We are extremely excited to announce the next version of Imply Analytics Platform, IAP 1.3.0, available immediately on our download page. This is one of our biggest releases to date and includes major updates for both Druid and Pivot.

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Announcing Imply 1.2.1

Vadim Ogievetsky · May 9, 2016

We are pleased to announce the latest version of the Imply Analytics Platform. This release focuses on improvements to Pivot and Tranquility as well as adding programmatic querying options to PlyQL.

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Programmatic PlyQL via HTTP, ODBC, and JDBC

Vadim Ogievetsky · May 4, 2016

Some time ago at Imply, we launched PlyQL, a command line utility that provides an SQL-like interface to Druid via Plywood. We heard a lot of positive feedback as many people prefer to use SQL over Druid’s native JSON-over-HTTP interface. The most common question we hear about PlyQL is how one can interface to it programmatically either from user created apps or from existing SQL based BI tools.

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Architecting Distributed Databases for Failure

Fangjin Yang · December 10, 2015

Everything is going to fail. If this is your first time working with or building out a distributed system, the fact that everything is going to fail may seem like an extremely scary concept, but it is one you will always have to keep in mind.

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A Tour Through the "Big Data" Zoo

Fangjin Yang · November 4, 2015

I recently read a great article by Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky that showcases the various techniques for visualizing and interacting with diverse data sets. I thought it may be useful to write something similar to showcase the various open source systems that exist in the “big data” space, including Druid, which is an open source data store I work on.

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Pivot: A Fast Data Exploration UI for Druid

Vadim Ogievetsky · October 26, 2015

A large part of what we do at Imply is help organizations build custom applications and visualizations on top of their data. While Druid is a powerful backend for powering applications, there are aspects of the development process that could definitely be easier. To enable people to better understand the power of Druid, we have released Pivot, an exploration UI that makes the most of the power of the Druid database.

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Announcing Imply: An Enterprise Solution for Druid and Interactive Analytics at Scale

Fangjin Yang · October 19, 2015

Today, Gian Merlino, Vadim Ogievetsky, and I are extremely excited to announce Imply, a company for interactive analytics at scale, centered around the Druid open source data store. We first began working on Druid at a startup called Metamarkets, and over the last few years, we’ve been proud to watch the project grow and take on a life of its own.

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