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Why We Raised $12M to Reimagine Business Dashboards
Featured

Why We Raised $12M to Reimagine Business Dashboards

Ask anyone how they feel about their dashboards, and you’re likely to get an earful of complaints. We believe this isn’t the fault of data teams: it’s that the tools and workflows for how dashboards are built must be reimagined.

Michael Driscoll
Michael Driscoll
on
August 4, 2022
Accelerating the Core Analysis Loop

Accelerating the Core Analysis Loop

Achieve flow in your work with tools that bring data insights at the speed of conversation.

Rill Developer is a tool to help data practitioners build data intuition by accelerating the core analysis loop. Try it out on github.

Marissa Gorlick
Marissa Gorlick
Marissa Gorlick
on
May 6, 2022
How to Create Roll-ups in Apache Druid

How to Create Roll-ups in Apache Druid

Neil Buesing crafted four hands-on examples of common Druid roll-up scenarios: roll-up comparison, Kafka ingestion, DataSketches, and custom time granularities.

Neil Buesing
Neil Buesing
Neil Buesing
on
December 22, 2021
Seeking the Perfect Apache Druid Rollup

Seeking the Perfect Apache Druid Rollup

Apache Druid Rollups improve storage and query performance. Keep these 8 important concepts in mind to use rollups effectively and avoid mistakes.

Neil Buesing
Neil Buesing
Neil Buesing
on
December 16, 2021
Apache Airflow for Orchestration and Monitoring of Apache Druid

Apache Airflow for Orchestration and Monitoring of Apache Druid

Part 2: Observability Logic for High Uptime SLAs

For pipeline management of critical applications, consider the lifecycle of your data. Use this conceptual framework to identify potential issues as early in the lifecycle as possible.

Scott Cohen
Rohith Reddy
Scott Cohen
Scott Cohen
on
October 21, 2021
Apache Airflow for Orchestration and Monitoring of Apache Druid

Apache Airflow for Orchestration and Monitoring of Apache Druid

Part 1: Technical Integration for Workflow

Monitoring the health of data pipelines and the underlying infrastructure-supporting applications and dashboards is mission critical for operational analytics. Learn how to set up our observability architecture using Apache Airflow integrated with Opsgenie and Slack.

Scott Cohen
Rohith Reddy
Scott Cohen
Scott Cohen
on
October 18, 2021
Fast Path to Streaming Data Analysis

Fast Path to Streaming Data Analysis

Geospatial Tutorial

This blog is a step-by-step how-to demo for streaming data into Rill’s platform for sub-second analysis. We selected aircraft telemetry data to answer time-series analytical questions.

Neil Buesing
Neil Buesing
Neil Buesing
on
October 12, 2021
The Guide to Apache Druid Architectures

The Guide to Apache Druid Architectures

A list of articles, customer stories, and reference architectures that best helped our team get up to speed learning about Apache Druid...

Michael Driscoll
Michael Driscoll
Michael Driscoll
on
October 4, 2021
Setting up Apache Druid on Kubernetes in under 30 minutes

Setting up Apache Druid on Kubernetes in under 30 minutes

Kubernetes is an orchestration engine which can run and manage containerized applications. Each application has different ways to autoscale...

Adheip Singh
Adheip Singh
Adheip Singh
on
October 1, 2021
Guide: Connect Looker to Druid and explore your data in real time

Guide: Connect Looker to Druid and explore your data in real time

This is a step-by-step guide on how to leverage Looker’s modeling and ad-hoc analytics with the performance of Druid to generate an operational analytics experience that is fast and interactive. 

Margie Roginski
Margie Roginski
Margie Roginski
on
July 22, 2021
5 Founders on building authentic data communities

5 Founders on building authentic data communities

Part 3 of our Modern Data Stack panel posed the question: "How do you build a data community that is authentic and real?" We considered the differences between audiences and communities, as well as differences between developer and user communities.

Marianne Jarvis
Marianne Jarvis
Marianne Jarvis
on
July 19, 2021
5 Founders on the biggest unsolved problems of the Modern Data Stack

5 Founders on the biggest unsolved problems of the Modern Data Stack

This next segment of the Modern Data Stack event had five data company founders respond to "the largest unsolved problems in modern data." They considered: What is the ROI of data, or of a dashboard? How do we reduce complexity? and more...

Marianne Jarvis
Marianne Jarvis
Marianne Jarvis
on
July 14, 2021
5 Founders define the Modern Data Stack

5 Founders define the Modern Data Stack

What does the "Modern Data Stack" really mean? What does it include? We hosted an in-person event in San Francisco to discuss the Modern Data Stack—ETL pipelines, quality monitoring, operational analytics, fast OLAP stores, headless BI, and more...

Marianne Jarvis
Marianne Jarvis
Marianne Jarvis
on
July 9, 2021
Guide: Connect Druid to Tableau for sub-second dashboards

Guide: Connect Druid to Tableau for sub-second dashboards

Leverage the speed of Druid in either a purpose-built analytics deployment or with the ease of your favorite analytics tools. If you have Tableau, use this short guide to walk you through connecting Tableau to Rill’s public Druid cluster.

Margie Roginski
Margie Roginski
Margie Roginski
on
July 6, 2021
How to achieve fast query speed with no DevOps maintenance

How to achieve fast query speed with no DevOps maintenance

The transition from on-prem to cloud has picked up speed. While just five years ago, companies were resisting moving to the cloud due to data security concerns, the more common question now is, “How can I move to the cloud as quickly and cost efficiently as possible?”

Margie Roginski
Margie Roginski
Margie Roginski
on
June 10, 2021
Introducing Rill Data’s BigQuery Connector

Introducing Rill Data’s BigQuery Connector

Apache Druid is an open source tool that comes with a standard set of connectors to ingest data from Kafka, Amazon S3, Google Cloud Storage, and Azure, and now with Rill Data ... BigQuery.

Margie Roginski
Egor Ryashin
Margie Roginski
Margie Roginski
on
June 3, 2021
Druid + Looker? Druid + Tableau? Leverage data interoperability for data visualization

Druid + Looker? Druid + Tableau? Leverage data interoperability for data visualization

If you are designing an analytics stack, it’s important to stay flexible. When it comes to analytics, you may choose a data warehouse such as BigQuery or Snowflake for periodic reporting on historical data, and you may choose an operational database such as Apache Druid or Pinot for ...

Margie Roginski
Margie Roginski
Margie Roginski
on
May 27, 2021
Apache Druid and Rill: better together

Apache Druid and Rill: better together

Apache Druid is an open source data store designed for high performance (sub-second) OLAP queries on large (terabyte) datasets. Learn how you can experience all of the benefits of Apache Druid's high performance real-time analytics database without the maintenance. 

Margie Roginski
Margie Roginski
Margie Roginski
on
May 20, 2021
When should I use Apache Druid? Try this checklist.

When should I use Apache Druid? Try this checklist.

Apache Druid is purpose built to generate high performance at low cost on a set of use cases that are becoming increasingly common: Operational Analytics. We've assembled the "Apache Druid Optimal Characteristics Checklist" to make it easy to understand the costs and benefits of using Druid for your use case.

Margie Roginski
Margie Roginski
Margie Roginski
on
May 13, 2021
Apache Druid Turns 10: The Untold Origin Story

Apache Druid Turns 10: The Untold Origin Story

Ten years ago today, the Druid data store was introduced to the world by Eric Tschetter, its creator, working at a small start-up named Metamarkets. Eric had left LinkedIn six months earlier to join us as the first full-time employee, and I was the CTO and co-founder, working ...

Michael Driscoll
Michael Driscoll
Michael Driscoll
on
May 1, 2021
Operational intelligence and the new frontier of data

Operational intelligence and the new frontier of data

At Rill, we believe the need for operational intelligence will dramatically expand in the coming years. In this post we lay out why operational intelligence matters now, its salient differences with traditional business intelligence, and why it demands new technology architectures.

Michael Driscoll
Michael Driscoll
Michael Driscoll
on
April 22, 2021
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