Here Comes the Data Lake Engine: Why I Joined Dremio
Jason Nadeau writes about the journey that led him to joining Dremio as the VP of marketing.
What Is a Data Lake Engine?
A Data Lake Engine delivers lightning-fast query speed and a self-service semantic layer operating directly against your data lake storage. Without moving data to proprietary data warehouses or creating cubes, aggregation tables and BI extracts. Just flexibility and control for Data Architects, and self-service for Data Consumers.
Cumulocity IoT DataHub Explained - Dremio
Overview of the Cumulocity IoT DataHub.
How To Use Inbound Impersonation
This tutorial helps users learn how to set up inbound impersonation.
Using a Data Lake Engine to Create a Scalable and Lightning Fast Data Pipeline
Learn how Dremio, the data lake engine, can help build a scalable and lightning fast data pipeline.
Cluster Analysis on Multiple Cloud Data Sources using Dremio and Python
This tutorial shows you how to perform cluster analysis on multiple cloud data sources using Dremio and Python.
Building Machine Learning Models on S3 and Redshift with Python
This tutorial shows you how to build ML models on multiple cloud data sources simultaneously using Dremio and Python
Simplifying the Data Pipeline
Learn how to leverage Dremio's data lake engine to simplify your data pipeline.
Building a JavaScript SDK for Dremio
Learn how to leverage Dremio's JavaScript SDK to make use of Dremio's APIs.
Configuring Dremio to Read S3 files leveraging AWS STS tokens
This how-to article goes through the steps to enable Dremio to access Amazon S3 files through a temporary STS key.
A Simple Way to Analyze Student Performance Data with Dremio and Python
In this tutorial we teach you how to use Dremio and Python to analyze student performance data in a simple way.
Dremio 4.0 – Technical Deep Dive
A deep dive into the new features of Dremio 4.0.
Using Dremio and Python Dash to Process and Visualize IoT Data
Ryan Murray shows us how he uses Dremio and Python Dash to process and analyze data from his homemade IoT ecosystem.
Accelerating Time to Insight with Dremio's Snowflake ARP Connector
Naren Sankaran showcases Dremio's ARP connector for Snowflake data sources.
Creating a Cloud Data Lake for a $1 Trillion Organization
The Dremio team sits down to discuss exactly how a trillion dollar organization can build a data lake.
Anomaly detection on cloud data with Dremio and Python
This tutorial will help you learn how to use Dremio and Python to discover anomalies in data stored in Amazon S3.
Datanami: Dremio is Best Big Data Startup (and Apache Arrow is a Project to Watch)
Dremio named Datanami's 2019 Editors' Choice for Best Big Data Startup
Announcing the Data Lake Engine (Dremio 4.0)
Today we are excited to announce the release of Dremio’s Data Lake Engine.
Gaining insights from cloud data lakes using Dremio and Python Seaborn
Using Dremio to access Amazon S3 data and visualize it using Python Seaborn.
Data Lake Machine Learning Models with Python and Dremio
Tutorial that shows users how to create machine learning models using Python and Dremio as a data lake engine.
Gensim Topic Modeling with Python, Dremio and S3
Tutorial explaining how to create a topic model using Gensim and Dremio on data stored in Amazon S3.
Announcing Dremio Hub
Dremio Hub is the center around which all things involving community-maintained assets will revolve.
How to Create an ARP Connector
Tutorial that helps users learn how to use the ARP framework to create custom data source connectors.
Dremio 3.3 – Technical Deep Dive
A deep dive into the new features of Dremio 3.3.
The Missing Link on Data Lakes
Data lakes provide an advanced solution for the modern data world, but without proper governance, order and ease of access its benefits might be overshadowed by its challenges. Dive in to learn more.
The Modern Data Platform Toolbox
Data lakes provide an advanced solution for the modern data world, but without proper governance, order and ease of access its benefits might be overshadowed by its challenges. Dive in to learn more.
Understanding Apache Arrow Flight
Arrow Flight provides a high-performance wire protocol for large-volume data transfer for analytics. Dive in to learn more.
Visualizing Amazon SQS and S3 using Python and Dremio
Learn how to use Python and Dremio to visualize data from your cloud data lake
Using Dremio and Python Dash to Visualize Data from Amazon S3
Learn how to use Python Dash to visualize Dremio data
Five Innovative Approaches To a Modern Data Platform
In this article we cover all the best practices to building a modern data platform on the cloud.
Cloud Data Lakes - What You Need to Know
In this article we show you everything you need to know to move your data to the cloud. Options, advantages, and much more.
Announcing Dremio 3.3
Dremio 3.3 includes many key features that continue to enhance the performance, security and administration of Dremio, providing faster time to insight and ease of access to data - see the highlights.
Connecting Qlik Sense to Azure Blob Storage
This tutorial shows you how to connect Qlik Sense to Azure Blob Storage using Dremio.
Analyzing historical Azure Stream Analytics data using Dremio
This tutorial shows you how to use Dremio to analyze historial Azure Stream Analytics data.
Cloud Data Lakes Explained by Dremio
A cloud data lake is a cloud-hosted centralized repository that allows you to store all your structured and unstructured data at any scale, typically using an object store such as S3 or Azure Data Lake Store.
Why there isn’t an Apache Arrow article in Wikipedia
In fact, the article has been submitted 4 times, not just by me but also by others, and declined each and every time.
Modern Data Platform and the Cloud
This is the second article in the series of building a Modern Data Platform.
Analyzing Multiple Cloud Data Sources using Dremio
Tutorial that helps users learn how to use Dremio to analyze data from multiple cloud data sources.
Four Key Elements of a Successful Data Lake
Data lakes are an agile, low-cost way for companies to store their data, but without the right tools, the data lake can grow stagnant and become a data swamp.
Characteristics, Whats, and Whys of the Modern Data Platform
If you Google 'modern data platform' you will get a lot of advertisement. Let’s try to agree on what modern data platform is.
Data Reflections: Accelerate your Queries Without Copies
Jesse Anderson and Dremio's Steven Phillips sit down to discuss various Apache projects and data reflection technology.
Microsoft Azure Storage Explained by Dremio
Overview of Azure Storage, explaining options, architecture and features.
Running SQL-Based Workloads in the Cloud Using Apache Arrow
At Strata 2019, Jacques Nadeau discussed how cloud-based SQL workloads can benefit from Apache Arrow.
How to Deploy Dremio on Amazon EKS
Tutorial that shows users how to deploy Dremio on AWS using EKS.
How to Deploy Dremio on Azure Kubernetes Service
Tutorial that shows users how to deploy Dremio on Azure Kubernetes Service.
It’s Time to Replace ODBC & JDBC
ODBC and JDBC were invented 27 years ago, Apache arrow arrived to bring the best-in-class performance in the big data world.
Unleash Your Data With a Data Lake Engine and Power BI on ADLS Gen2
Tutorial that teaches users how to visualize data from different sources using Power BI and Dremio.
Self-Service Data for the Data Lake
Kelly Stirman discusses how Dremio enables self-service data in the data lake, as well as provideing a hands-on demonstration.
Creating a Regression machine learning model using ADLS Gen2 data
Learn how to create a machine learning regression model using data stored in ADLS using Python and Dremio.
Building a Machine Learning Classifier with ADLS Gen2 and HDFS using Dremio
Learn how to build a Machine Learning Classifier with ADLS Gen2 and HDFS using Dremio.
What is ADLS Gen2 - and why it matters
The second generation of ADLS, also known as ADLS Gen2, brings together all the great features of ADLS Gen1 and Azure Blob Storage.
Building a Cloud Data Lake on Azure with Dremio and ADLS
Learn how to create a cloud data lake using Dremio and ADLS
Clustering and Analyzing HDFS and Hive Data Using scikit-learn and Dremio
Tutorial that helps users learn how to cluster data from different sources using scikit-learn and Dremio.
Dremio 3.2 - Technical Deep Dive
A deep dive into the new features of Dremio 3.2.
How to set up HDFS and HIVE Impersonation
Tutorial that helps users learn how to set up HDFS and HIVE impersonation .
Azure Data Lake Analytics Explained by Dremio
Overview of Azure Data Lake Analytics (ADLA), explaining ADLA architecture and features. Understand your options.
Interactive Data Science and BI on the Hadoop Data Lake
Our VP of Marketing Kelly Stirman discusses how Dremio lets users build data science and BI workflows on their Hadoop data lake.
Announcing Dremio 3.2
Dremio 3.2 includes over 200 improvements, including support for ADLS Gen2, big speed improvements on S3 and ADLS via predictive pipelining, and support for Kubernetes and Helm deployments - see the highlights.
Unlocking Data-as-a-Service for ADLS and Elasticsearch Using Dremio and Qlik Sense
Tutorial that helps users learn how to join data from ADLS and Elasticsearch Dremio and Qlik Sense.
Running SQL Based Workloads in The Cloud at 20x - 200x Lower Cost Using Apache Arrow
Jacques Nadeau discusses the impacts of Apache Arrow and Gandiva when running SQL workloads in the cloud.
Data-as-a-Service on Azure Data Lake Store with Apache Superset and Dremio
Tutorial that helps users learn how to gain insights from data stored ADLS using Dremio and Superset.
Unlocking Data-as-a-Service for Apache Superset using Dremio
Tutorial explaining how to visualize data from two different data sources using Dremio and Superset.
Unleashing Data-as-a-Service for ADLS with Dremio and R
Tutorial that helps user learn how to analize data stored in ADLS usign Dremio and R.
Creating a Classification ML model using data stored in ADLS
Learn how to create a Classification ML model using data stored in ADLS using Dremio
Azure Data Lake Store Explained by Dremio
Overview of Azure Data Lake Store (ADLS), explaining ADLS architecture, features and comparing with ADLS Gen2. Understand your options.
Data Science Across Data Sources With Apache Arrow
Jacques Nadeau.
Enabling Data-as-a-Service for Azure, PostgreSQL and Tableau
Use Dremio to work with data stored in Azure Blob Storage and PostgreSQL.
Sentiment Analysis with PyTorch and Dremio
Tutorial that helps users learn how to do sentiment analysis with Dremio and PyTorch.
Analyzing Multiple Data Sources Simultaneously with Dremio and DBVisualizer
Tutorial that helps users learn how to use Dremio with DBvisualizer.
Using Dremio to Fix Data Inconsistency
Tutorial that helps new users learn how to use Dremio to fix data inconsistencies
Enabling Data-as-a-Service for AWS and R
Tutorial that helps users learn how to use Dremio with Amazon Web Services and R.
Analyzing Hive data using Dremio and Keras
Tutorial that helps users learn how to use Dremio with Keras.
Dremio 3.1 - Technical Deep Dive
A deep dive into the new features of Dremio 3.1.
Success Story - How Hotmart uses Dremio to gain insights from data, faster.
How Hotmart uses Dremio to gain insights from data, faster.
Announcing Dremio University
Dremio Launches Free Online Training Courses for Data Engineers, Analysts, and Data Scientists.
Enabling Data-as-a-Service for Postgres and SQL Server
Tutorial that helps users learn how to use Dremio with relational data sources and Tableau.
Announcing Dremio 3.1
Dremio 3.1 includes many new features and performance improvements - see the highlights.
Analyzing Data With TIBCO Spotfire and Dremio
Tutorial that helps user learn how to analize data using TIBCO Spotfire and Dremio.
Working with Dremio and LDAP/AD Authentication
Tutorial that helps users learn how to integrate Dremio with LDAP/AD.
Analyzing Amazon Redshift with Dremio and Python
In this tutorial, learn how you can use Dremio to bridge the gap between Azure Data Lake Store and Tableau.
Starting Apache Arrow
Our CTO Jacques Nadeau sat down for a fireside chat with Wes Mckinnney, discussing the past, present, and future of Apache Arrow.
Analyzing MySQL data with Dremio and Python
Tutorial that helps users learn how to use Dremio with MySQL and Python.
Analyzing MongoDB Atlas with R and Tableau
Tutorial that helps users learn how to use Dremio with MongoDB Atlas and R.
Dremio 3.0 - Technical Deep Dive
A deep dive into the new features of Dremio 3.0.
Announcing Dremio 3.0
Dremio 3.0 is a major release that includes many new features, performance improvements and security enhancements - see the highlights.
High Performance Parallel Exports
Tutorial that helps users learn how to use Dremio's high performance parallel exports.
Enterprise Data Catalog Enhancements
Tutorial that helps users learn how to use Dremio's enhanced data catalog features.
Dynamic Security Controls - Apache Ranger Integration
Tutorial that helps users learn how to integrate Dremio with Apache Ranger.
Analyzing Hive Data with Dremio and Python
Tutorial that helps users learn how to use Dremio with Hive and Python.
Dremio 2.1 - Technical Deep Dive
A deep dive into the new features of Dremio 2.1.
Adding a User Defined Function to Gandiva
Learn how to add User Defined Functions to Gandiva.
Using Python to Analyze Data with Dremio deployed in Docker and Kubernetes
Tutorial that helps new users learn how to deploy Dremio on Docker.
Gandiva Initiative Update: Improving SQL Projection Performance by 70x
Exploring performance improvements for SQL processing in Dremio based on Gandiva Initiative for Apache Arrow.
Conquering Slow, Dirty and Distributed Data with Apache Arrow and Dremio
At the 2018 Data Science Summit, CEO Tomer Shiran spoke about Dremio and Apache Arrow, outlining how projects like Pandas are utilizing Arrow to achieve high performance data processing and interoperability across systems.
Join Elasticsearch and MongoDB with Qlik Sense
Dremio unlocks SQL on Elasticsearch and MongoDB for Qlik Sense.
Using LLVM to Accelerate Processing of Data in Apache Arrow
Dremio CEO Tomer Shiran was a guest on the Software Engineering Daily podcast to talk about how Dremio works and who it benefits.
Unlocking Azure Data Lake Store for Power BI
Learn how Dremio unlocks ADLS for Power BI
Introducing the Gandiva Initiative for Apache Arrow
In-depth technical description of Dremio's Gandiva Initiative for Apache Arrow.
The Origin & History of Apache Arrow
A background and overview of the Apache Arrow project from the PMC Chair, Jacques Nadeau.
Apache Drill Explained by Dremio
Overview of Apache Drill, including columnar data representation, schema discovery, SQL compatibility with non-relational databases, and more.
Apache Arrow Explained by Dremio
Overview of Apache Arrow, including in-memory performance, columnar data representation, vectorized query processing, and more.
Introducing the Dremio Data Science Index
Read more about the methodology behind our Data Science Index – which tracks the popularity of data science tools.
Apache Arrow SF Meetup, May 2018: Vectorized Query Processing With Arrow
Dremio software engineer Siddharth Teotia provides an overview of Apache Arrow and breaks down the benefits of vectorized query processing at our May 2018 Apache Arrow SF meetup.
Apache Arrow SF Meetup, May 2018: Arrow Integration with Spark
IBM software engineer Bryan Cutler provides an overview of Apache Arrow integration with Spark.
Apache Arrow SF Meetup, May 2018: Arrow In Theory, In Practice
An in-depth walkthrough of Apache Arrow with Dremio CTO Jacques Nadeau from the May 2018 Apache Arrow SF meetup.
Evolve 2018: Pitch Your Tech in 5 Minutes
Dremio's CMO Kelly Stirman pitches the benefits of Dremio at Evolve 2018.
Analyzing Azure Data Lake Store and Tableau
Learn how Dremio bridges the gap between ADLS and Tableau
Making Big Data Self-Service for Users
Kelly Stirman sits down with Truth in IT to discuss how Dremio can help make big data self-service for it's users.
Dremio 2.0 - Technical Deep Dive
A deep dive into the new features of Dremio 2.0.
Announcing Dremio 2.0 – Starflake Reflections, REST APIs, and more!
Dremio 2.0 is a major release that includes many new features, performance improvements, and stability enhancements - see the highlights.
Introducing the REST API
Tutorial that helps users play with the REST API in Python.
Introduction to Starflake Data Reflections
Behind the scenes, invisible to end users, a relational cache comprising data materializations, also known as Data Reflections™, enables Dremio to accelerate queries from users and tools.
Connecting Looker to Dremio
Learn how to Connect Looker to Dremio to gain access to NoSQL databases like MongoDB and Elasticsearch, as well as Data Lakes running on Hadoop, Amazon S3, and Azure ADLS.
Self-Service Data for the Data Lake
CMO Kelly Stirman provides an overview of data lake challenges and how users can navigate the growing complexity of self-service data with help from Dremio.
Data Access for Data Science
CTO Jacques Nadeau spoke at the 2018 AnacondaCON, detailing how Apache Arrow and Dremio enable users to access and analyze data across disparate data sources.
Making BI Work with a Data Lake
CMO Kelly Stirman discusses how to incorporate Business Intelligence into Data Lakes, and then provides some real world examples using Dremio.
The Winter Olympics Story: How I Did It
Learn how I built the winter olympics data analysis story using Dremio.
Making Data Fast and Easy to Use with Data Reflections
Tomer Shiran discusses data reflections and how they can help speed up data access and analysis.
Trump Twitter Sentiment Analysis: How I Did It
Learn how we built a twitter sentiment analysis using Dremio, Tableau, and more.
How New Companies Can Contribute to Open Source
Jacques Nadeau talks with Swapnil Bhartiya, founder of TFiR, about the ways new companies can contribute to Open Source.
Connecting Tableau to MongoDB
Tutorial that helps users learn how to use Dremio with MongoDB and Tableau.
Vectorized Query Processing Using Apache Arrow
Dremio software engineer Siddharth Teotia provides an overview of Apache Arrow and breaks down the benefits of vectorized query processing.
Building an Analytics Stack on AWS with Dremio
CEO Justin Bock of Bock Corporation sits down with Dremio's Kelly Stirman to discuss building an analytics stack on AWS using Dremio.
Integrating Tableau with Amazon S3
Learn how to use Dremio with Amazon S3 and Tableau
Analyzing Amazon S3 with Qlik Sense
Tutorial that helps users learn how to use Dremio with Amazon S3 and Qlik Sense.
Jacques Nadeau Discusses Dremio and Big Data with theCube
CTO and Co-Founder Jacques Nadeau sits down with theCube to discuss Dremio's role in the future of Big Data.
Analyzing MongoDB with Qlik Sense
Tutorial that helps users learn how to use Dremio with MongoDB and Qlik Sense.
Analyzing Hadoop with Qlik Sense
Tutorial that helps users learn how to use Dremio with Hadoop and Qlik Sense.
Data Visualizations with Dremio, D3 and Node
Tutorial that shows users how to connect Dremio to Node and create data visualizations with D3 in browser.
The Heterogeneous Data Lake
A webinar by Tomer Shiran about the rise of Heterogeneous Data.
The Columnar Roadmap: Apache Parquet and Apache Arrow
A presentation by Julien Le Dem about the Columnar Roadmap using Apache Parquet and Apache Arrow.
Summary of Dremio Series B Coverage
Coverage of Dremio's Series B funding announcement.
Java Vector Enhancements for Apache Arrow 0.8.0
Technical performance review of enhancements to Java vectors in Apache Arrow 0.8.0
Simplifying and Accelerating Data Access for Python
Sudheesh Katkam discusses how you can use Python with Dremio to simplify and accelerate access to several different data sources together.
Using Apache Arrow, Calcite and Parquet to build a Relational Cache
Jacques Nadeau talks about how layering in-memory caching, columnar storage and relational caching can combine to provide a substantial improvement in overall data science and analytical workloads.
Improving Python and Spark Performance and Interoperability with Apache Arrow
A talk with Julien Le Dem and Ji Lin about using Apache Arrow to improve the performance of Apache Spark and Python while scaling up data processing.
Data Engineering Explained by Dremio
Overview of data engineering, including data engineering trends and history, and how it compares with data science. Understand your options.
Data Warehouses Explained by Dremio
Overview of data warehouses, explaining data warehouse architecture, OLTP vs. OLAP, and comparing data warehouse technologies. Understand your options.
Data Pipelines Explained by Dremio
Overview of data pipelines and OLTP vs. OLAP, explaining what they do, and what technologies are typically involved. Understand your options.
ETL Tools Explained by Dremio
Overview of ETL tools comparing open source, enterprise, and custom ETL, as well as cloud services. Understand your options.
Analyzing Elasticsearch With Qlik Sense
Tutorial that helps new users learn how to use Dremio with Qlik and Elasticsearch
Arrow C++ Roadmap and pandas2
Arrow C++ roadmap and Pandas2 talk from Wes McKinney, Arrow committer and creator of Python Pandas.
Apache Arrow: In Theory, In Practice
A talk through Apache Arrow with Dremio CTO Jacques Nadeau.
Analyzing MongoDB With Power BI
Tutorial that helps new users learn how to use Dremio with Power BI and MongoDB
Getting Started With Data Reflections
Tutorial that helps new users learn how to use Dremio's Data Reflections.
Dremio 1.3 - Technical Deep Dive
A deep dive into the new features of Dremio 1.3.
Analyzing web server logs with Dremio, Apache Spark, and Kotlin
Tutorial that helps new users learn how to use Spark and Kolin with Dremio.
New Options for Moving Analytics to the Cloud
A Dremio webinar that explores new options for moving your analytics to the cloud.
Connecting Your Elasticsearch Cluster To Dremio
Tutorial that helps new users connect their Elasticsearch clusters to dremio.
Lucene Expression Push-Downs into Elasticsearch via SQL with Dremio
Use full Lucene syntax from your SQL queries with Dremio and Elasticsearch.
Setting Up Dremio On Google Cloud Platform With Oracle
Tutorial that helps users set up Dremio on Google Cloud Platform with Oracle.
Intro to Self-Service Data With Dremio
A webinar that introduces new users to self-service data with Dremio.
Installing Dremio and Oracle Database on the Oracle Cloud
Installing Dremio and Oracle Database on the Oracle Cloud
Use SQL To Query Multiple Elasticsearch Indexes
Use SQL to query multiple Elasticsearch indexes.
Dynamic Security Controls - Masking Sensitive Data Using Dremio
Tutorial that helps user learn how to mask data using Dremio.
Installing Dremio and Oracle Database on Microsoft Azure
Tutorial that helps user set up Dremio on Azure with Oracle.
Compiling SQL to Elasticsearch Painless
Dremio automatically compiles SQL queries into Elasticsearch Painless scripts.
Building A Recommender With Scikit-Learn And Dremio Virtual Datasets
Tutorial that helps new users learn how to build a recommender with scikit-learn and Dremio on data in Postgres and MongoDB.
Setting Up Dremio On AWS With Oracle
Tutorial that helps user set up Dremio on AWS with Oracle.
Running SQL Joins in Elasticsearch With Dremio
Tutorial that helps new users learn how to perform SQL joins on Elasticsearch using Dremio.
Combining Data From Multiple Datasets
Learn how to combine data from multiple datasets using Dremio with S3 and Tableau
Unlocking Tableau on Elasticsearch
Dremio unlocks Tableau on Elasticsearch.
Unlocking SQL on Elasticsearch
Dremio unlocks SQL on Elasticsearch.
Analyzing Book Reviews With Dremio, SQL, and R
Tutorial that helps users learn how to use R and Dremio together.
Data Curation With Dremio
Tutorial that helps new users learn how to curate data with Dremio.
Visualizing Tweet Sentiment With Excel, SQL, and Dremio
Tutorial explaining how to visualize Tweet sentiment with Excel, SQL, and Dremio.
Analyzing Tweet Sentiment With SQL and Dremio
Tutorial explaining how to analyze Tweet sentiment with SQL and Dremio.
How To Share A Query Profile
Tutorial explaining how to share a query profile in Dremio.
Using Pandas With Dremio For Quantitative Sports Betting
Tutorial explaining how to use Pandas with Dremio.
Adding Users to Dremio
Tutorial that helps new users work with administrative features like adding users to Dremio.
Accelerating Analytics For Postgres With Dremio
Tutorial that helps new users learn how to use Dremio with PostgreSQL.
Looking Back At How We Exited Dremio From Stealth
Our CEO reflects on two years of stealth and exiting Dremio from stealth.
Accelerating TensorFlow Data With Dremio
Using Dremio to make analytics with TensorFlow fast.
Visualizing Your First Dataset With Tableau
Tutorial that helps new users learn how to visualize their Dremio datasets with Tableau.
Working With Your First Dataset
Tutorial that helps new users learn how to work with Dremio datasets.
Getting Oriented to Dremio
Tutorial that helps new users get oriented to the basics of Dremio.
Summary of Dremio Launch Coverage
Coverage of Dremio's launch on July 19, 2017.
Recognizing A New Tier
Dremio's co-founder describes his vision for starting the company and the future of data analytics.
What Are Data Pipelines?
We’ve published a new page - What Are Data Pipelines?
What is a Data Warehouse?
We’ve published a new page - What is a Data Warehouse?
ETL Tools Explained
We’ve published a new page - ETL Tools Explained
What is Data Engineering?
We’ve published a new page - What Is Data Engineering?
BI on Big Data: What are your options?
Deciding what combination of technologies will yield the best ‘BI on Big Data’ experience can be a major challenge for data professionals.
What are Dremio and Apache Arrow?
CTO and co-founder Jacques Nadeau sits down with Datameer to discuss the launch of Apache Arrow and the future of Dremio.
Introducing Apache Arrow: Columnar In-Memory Analytics
Apache Arrow establishes a de-facto standard for columnar in-memory analytics which will redefine the performance and interoperability of most Big Data technologies.
Tuning Parquet file performance
A brief discussion about how changing the size of a Parquet file’s ‘row group’ to match a file system’s block size can effect the efficiency of read and write performance.