Name: Dremio: The Forever-Free Lakehouse Platform
Uploaded: 2022-03-01T16:38:48.000Z
Duration: 1 min 9 s
Description: Built for SQL, with a Git-like experience, and an open source foundation – Dremio’s forever-free lakehouse platform helps you drive better decisions, by giving data consumers easier access to the freshest, most complete data, without waiting. Learn more: https://www.dremio.com/platform.

Help Desk

Web and Video Conferencing

Customer Support

Automation Testing

Development

Higher Education

K-12 Online Learning

Education

Barcode

Business Intelligence (BI)

Collaboration

File Sharing

Smart Spaces

Streaming Analytics

Enterprise

Accounting

Financial Close

Finance and Accounting

Applicant Tracking

Background Check

Corporate Learning Management

Diversity, Equity, and Inclusion (DEI)

HR Management

Payroll

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

Business Internet Service Providers (ISPs)

Cloud Cost Management

Cloud Storage

Data Preparation

Debugging

Edge Computing

Fraud Detection

Integration Platform as a Service (iPaaS)

License Management

Managed Hosting

Managed Security Service

Modular Storage Area Network (SAN)

Network Function Virtualization (NFV)

Network Monitoring

Network Performance Monitoring

Packet Analyzer

Runtime Application Self-Protection

Secure Web Gateway

Virtual Private Cloud (VPC)

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

App Store Optimization (ASO)

Community

Content Experience

Content Management

Creative Collaboration

Customer Journey Mapping

Digital Asset Management

Email Marketing

Marketing Automation

Online Proofing

Public Relations (PR)

Sales and Marketing Automation

Social Media Management

Social Media Marketing

Survey & Forms Building

Video

Web Analytics

Marketing

Interactive Whiteboard

Project Management

Professional Services

Customer Communication Management

Customer Relationship Management (CRM)

Sales Content Management

Sales

Chiropractic

Civil Engineering

ID Card

Moving Software

Nonprofit Fundraising

Oil and Gas

Tax Practice Management

Vertical-Specific

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### Query Performance and Execution
Users consistently highlight Dremio's query performance and execution as standout features, praising its ability to deliver lightning-fast query speeds and optimize data retrieval processes. The platform's efficient query engine and execution capabilities have garnered positive feedback, with users commending its ease of use and the significant performance improvements it offers. Additionally, Dremio's focus on enhancing query performance through features like reflections has been well-received, contributing to a smoother and more efficient data querying experience for users across various data sources.

### Data Access and Integration
Users generally believe that Dremio excels in data access and integration functionality. The platform is praised for its ease of configuring multiple data sources and creating virtual datasets that enable unions across them. Users appreciate the performance for data retrieval, highlighting Dremio's ability to handle terabytes of data efficiently. However, some users express concerns about the lack of certain database connectors and suggest improvements in the user interface for a more streamlined experience. Despite these minor drawbacks, Dremio is recognized for its innovative approach to scalable data access and its contribution to enhancing productivity within organizations.

### Performance Optimization
Users consistently highlight Dremio's performance optimization as a standout feature, emphasizing its ability to accelerate queries and enhance data processing speed. The platform's performance optimization capabilities have garnered praise for streamlining analytics and machine learning processes, enabling efficient data insights without the need for extensive data engineering skills. Additionally, users appreciate Dremio's responsiveness in managing high workloads and delivering fast response times for numerous management dashboards, showcasing its effectiveness in optimizing performance across diverse use cases.

### Data Lakes and Warehousing
User feedback on Dremio's data lakes and warehousing capabilities varies across reviews. While some users praise Dremio for its ability to provide direct and fast access to data in the data lake, others express concerns about limitations when dealing with large datasets and the need for better support for certain data formats like Iceberg. The consensus seems to be that Dremio offers a solid foundation for connecting applications and BI tools to data lakes, but there are areas where improvements could enhance its performance and usability in data warehousing scenarios.

### Database and Storage Technologies
User consensus seems to be that Dremio's database and storage technologies capabilities are a strong point. Reviewers appreciate the ease of accessing data from various platforms like HDFS, Oracle RDBMS, and SQL Server. The standardized semantic layer eliminates the need for data duplication and accelerates queries, enhancing overall data management efficiency. However, some users have highlighted areas for improvement, such as the lack of certain database connectors and the need for UI enhancements. Despite these minor drawbacks, Dremio's database and storage technologies receive positive feedback for their ability to streamline data access and enhance data lake utilization.

### Data Management and Retrieval
Users generally praise Dremio's efficient data management and retrieval capabilities. They appreciate the platform's ability to provide fast and direct access to data in a data lake, reducing the time required to access data and minimizing the IT footprint. While some users note the manual management required for reflections and the lack of a managed service on the Microsoft Azure platform as drawbacks, overall, Dremio's user-friendly interface and modernized approach to data management have garnered positive feedback. The platform's support for creating semantic layers without IT involvement and its adaptability to various use cases, from management reporting to AI use cases, have contributed to its favorable reception among users.

### SQL and BI Tools
Opinions on Dremio's SQL and BI tools capabilities vary among users. While some praise the ease of use and the ability to connect to multiple data sources effortlessly, others have highlighted areas for improvement, such as the learning curve associated with the interface and the need for enhanced usability features. Users appreciate the SQL-based approach and the data virtualization aspect, which simplifies access to heterogeneous sources. Additionally, the platform's ability to accelerate ad-hoc and self-service queries has been positively noted. However, there are suggestions for enhancements to make the tool more user-friendly and efficient in handling complex queries.

### Analytics and Insights
Users across various industries have unanimously praised Dremio's robust analytics and insights capabilities. The tool's intuitive interface and powerful features have enabled organizations to derive valuable insights quickly and efficiently. Clients have highlighted the tool's ability to streamline data analysis processes, leading to significant cost and time savings. Additionally, Dremio's support team has been commended for their responsiveness and assistance in leveraging the tool's analytics functionalities effectively. The consensus among users is that Dremio excels in providing advanced analytics solutions that drive informed decision-making and enhance overall business performance.

### Advanced Analytics and Machine Learning
Users consistently praise Dremio for its robust capabilities in accelerating analytics and machine learning tasks. The tool's ability to streamline data preparation for AI and ML purposes, along with providing a self-service DataHub for business users, has garnered positive feedback. Dremio's role as a foundational layer in the analytics stack, offering direct SQL access to vast amounts of data and connectivity to advanced analytic, ML, and data visualization tools, has been highlighted as a key strength by users. This emphasis on enhancing analytics and machine learning workflows aligns well with users' strategies to reduce reliance on specialized data warehouse technologies.

### Data Transformation and Processing
Users generally praise Dremio for its streamlined data transformation and processing capabilities. The consensus among reviewers is that Dremio simplifies the data transformation process, allowing for quick exploration and structuring of large datasets without the need for extensive IT involvement. The platform's ability to reduce ETL developments and provide fast query processing times has been highlighted as a significant advantage by users. Additionally, Dremio's feature set, including reflections for enhanced performance and a user-friendly interface, has garnered positive feedback for enabling efficient data processing and transformation tasks.

### Data Virtualization and Exploration
Users consistently praise Dremio's data virtualization and exploration capabilities, highlighting its ability to provide a unified query layer for exploring disparate data sources. The platform's data virtualization and democratization features have been particularly well-received, with users noting the simplicity of the UI and the low entry threshold for end users. Dremio's focus on central data virtualization and democratizing data has resonated positively with users, especially those with a SQL background. Additionally, the platform's technical edge in enabling data exploration among heterogeneous sources has been commended for streamlining data quality analysis tasks.

Users have made several recommendations based on their experiences with Dremio as a centralized data platform for organizations. The most common recommendations include utilizing ODBC or pyarrow flight for queries over the Python API to improve performance. Running a proof of concept to gain confidence in Dremio is another frequent suggestion. Lastly, users advise trying out the community AWS Edition of Dremio as it provides most, if not all, of the necessary features required by organizations. Additionally, users appreciate the thorough documentation provided by Dremio, which aids in understanding and effectively utilizing its features and functionalities.

Dremio has proved useful in solving various data-related business problems. Users have found that Dremio's ability to break down data silos is a valuable asset. Its architecture unlocks data in the data lake and warehouse, making it more accessible and usable by a larger population. Additionally, users can perform queries across multiple data sources, resulting in speedy data analytics and increased efficiency.

Moreover, Dremio's user-friendly UI has helped business users create semantic layers on top of the data lake without IT involvement, resulting in significant time-to-market advantages. The tool simplifies the process of Data Analytics and provides superior performance compared to legacy technology stacks. Furthermore, its direct SQL access to PB of data allows users who like using SQL to query their data fast, despite it being stored in different locations with different formats. Finally, Dremio helps organizations be more resilient through Black Swan events by guiding their insights and actions based on data, resulting in quicker decision-making.

Easy to use and deploy: Multiple reviewers found Dremio to be an easy-to-use tool for data analytics, with a simple deployment process. Users have been impressed with the ease of getting started with the software, especially for those without an IT background.

Great customer support: Several users praised Dremio's customer support team for their responsiveness and knowledge in addressing queries. The professional services provided by Dremio were also commended as being world-class.

Ability to bring silos of data together: Many reviewers appreciated how Dremio allowed them to bring various formats and sources of data from different departments into a single platform. This feature made it easy for both analysts and non-analysts to search, find, and query data effectively without going through the ETL/ELT process.

Steep Learning Curve: Some users have found Dremio difficult to use due to a steep learning curve. They report that while the software is not unbearable, it can take some time to get used to all of its features and functionality.

Limitations on Columns and Fields: The hard limits on the number of columns and fields in Dremio can be problematic for certain use cases, according to some users. This limitation may prevent them from using the software as effectively as they would like.

Lack of Support for Database Views and External Decryption Libraries: A significant disadvantage reported by some users is the lack of support for database views and external decryption libraries. This limitation can create issues when trying to integrate with other tools or work with specific types of data.

Dremio, from the company of the same name in Santa Clara, is described as a data lake engine. Dremio operationalizes data lake storage and speeds analytics processes, boasting a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts via a governed self-service layer. According to the vendor, this results in fast, easy data analytics for data consumers at the lowest cost per query for IT and data lake owners. It is available on-premise, via AWS, or via Azure.

Dremio

Data virtualization tools provide a virtual abstraction layer for multiple sources of data without copying or moving the data. This layer hides the technical aspects of stored data like location, structure, access language and storage technology. Data virtualization tools allow many different data sources to act as a single, consistent source for data consumers.

Data Virtualization

Dremio Demo | Data Reflections

Experience the power of Dremio with a demo of the Data Reflection feature. Data Reflections are physical optimized Parquet data structures that Dremio invisibly and automatically incorporates into query plans to provide maximum query speed. Through this feature, you can accelerate BI dashboarding and reporting queries with Dremio.

Data Reflections are an important part of Dremio’s data platform, which provides a unified solution for data lakehouse and data warehouse architectures. This platform helps you to manage your data lake engine, create a governed self-service layer, and democratize access to data for analysts and scientists. 

Using Data Reflections in Dremio, you can easily incorporate the data structures into your query plans for maximum query speed. You can also apply filters on your queries to improve performance even further. This allows you to quickly access the insights you need from your data lake engine without having to manually configure complex settings or wait for long query times. 

To try out Data Reflections in Dremio yourself, simply follow this link: http://bit.ly/36J27iw  With this easy-to-use feature, you’ll be able to experience firsthand how quickly and efficiently you can perform analytics queries on large datasets stored in your data lakehouse or warehouse architecture. Get started today! 

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Blog: https://bit.ly/2DgyR9B
Questions?: https://bit.ly/30oi8tX 
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Dremio Demo | How to Use Data Reflections to Speed Up Queries

Dremio Demo | Driving Insights from the Azure Data Lake

Superset Live Demo: High-performance Datalake Visualization with Dremio and Superset

Live sobre o que são Data Lakes de fato e como construí-los utilizando o incrível Dremio.

Fontes de dados analisadas na Demo: https://registry.opendata.aws/nyc-tlc-trip-records-pds/

Post sobre o Dremio: https://medium.com/data-hackers/o-que-%C3%A9-e-como-funciona-o-dremio-4ff2c7a6d119

Vagas na DataSprints: https://hipsters.jobs/company/1925/data-sprints/

SprintTalks #2 - DataSprints - Enterprise Data Lakes com Dremio

Deploy Data Lake Insights with Dremio AWS Edition

Do you want to maximize the power of your data? With Dremio AWS Edition, you can do just that! Deploying the new Dremio AWS Edition will give you lightning-fast queries, a service-like experience and unparalleled AWS infrastructure cost efficiency—all for free. In this step-by-step demo, we'll show you how to deploy and configure the AWS Edition. 

Dremio is a data lake engine that operationalizes your data lake storage and speeds up your analytics processes. It provides fast, easy data analytics for data consumers at the lowest cost per query for IT and data lake owners. Dremio also democratizes data access for data scientists and analysts via a governed self-service layer. 

Ready to try it out? Follow this link to deploy for free: http://bit.ly/36J27iw 

Connect With Us! 
For more information about Dremio, stay connected with us on social media or our community forum. We're active on Twitter (https://bit.ly/30pcpE1), LinkedIn (https://bit.ly/2PoqsDq), Facebook (https://bit.ly/2BV881V), Community Forum (https://bit.ly/2ELXT0W), Github (https://bit.ly/3go4dcM), our Blog (https://bit.ly/2DgyR9B) or visit our Website (https://bit.ly/2XmtEnN). If you have any questions, don't hesitate to reach out to us via Questions?: https://bit.ly/30oi8tX 

Take advantage of Dremio's Data Lakehouse architecture today by deploying the new Dremio AWS Edition! This step-by-step demo will show you how to get lightning-fast queries, a service-like experience and unparalleled AWS infrastructure cost efficiency—all for free! Start driving insights from your data lake today by clicking http://bit.ly/36J27iw #DataLakeHouse #DataWarehouse #DataLake #DataLakeEngine #Cloud 

Connect with us!

Twitter: https://bit.ly/30pcpE1
LinkedIn: https://bit.ly/2PoqsDq
Facebook: https://bit.ly/2BV881V
Community Forum: https://bit.ly/2ELXT0W
Github: https://bit.ly/3go4dcM
Blog: https://bit.ly/2DgyR9B
Questions?: https://bit.ly/30oi8tX 
Website: https://bit.ly/2XmtEnN

Deploying Dremio AWS Edition Step-by-Step Demo | Dremio Video Tutorial

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Launch Dremio from AWS Marketplace: Step-by-Step Demo

Dremio is the easy and open data lakehouse platform, enabling lightning-fast SQL on S3, ADLS and operational databases. Preset Cloud is a cloud-hosted version of Apache Superset, the leading open source data exploration and visualization platform. In this live demo, we’ll showcase how you can quickly get large datasets in your lakehouse, connect Preset to Dremio, and build a compelling dashboard in just a few minutes and all for free. Speed and ease-of-use are at the core of both platforms.

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Dremio Cloud: https://www.dremio.com/

Preset Cloud is a managed service for Apache Superset. Get started with our forever free tier at https://preset.io/product/

Preset Managed Private Cloud brings the seamless Superset experience into your own Private Cloud. Learn more here: https://preset.io/preset-managed-private-cloud/

More Resources: https://www.preset.io/resources/

Data to Dashboard Using Dremio Cloud and Preset Cloud

Demo - Dremio’s Data Lakehouse

Dremio Cloud Demo: Learn How to Get Started with the Data Platform in 5 Minutes

Subsurface LIVE Winter 2022 Keynote Demo with Jason Hughes - Boost SEO Rankings

Dremio: The Forever-Free Lakehouse Platform

Built for SQL, with a Git-like experience, and an open source foundation – Dremio’s forever-free lakehouse platform helps you drive better decisions, by giving data consumers easier access to the freshest, most complete data, without waiting. Learn more: https://www.dremio.com/platform.

Data Visualization

Data Visualization software features help clients and businesses better visualize and present data.

Data Visualization Options

Provides a wide range of customizable data visualization options such as charts, graphs, maps, and tables to effectively present data.

Interactivity

Enables users to interact with the visualizations by clicking, hovering, zooming, or filtering to explore the data further.

Data Import and Export

Allows users to easily import data from various sources like databases, spreadsheets, CSV files, and APIs, and export visualizations for sharing or further analysis.

Dashboard Creation

Allows users to create interactive dashboards by combining multiple visualizations and data components into a single layout for a comprehensive view of data.

Customization Capabilities

Offers options to customize colors, styles, labels, fonts, and other design elements to tailor visualizations to specific needs and branding.

Data Filtering and Sorting

Enables users to filter and sort data within visualizations based on specific criteria to focus on relevant information and trends.

Project Collaboration Tools

Provides features for multiple users to collaborate on data visualizations simultaneously, share insights, and work on projects together.

Real-time Data Updates

Supports real-time data streaming and updates to ensure that visualizations reflect the most current information and changes.

Cross-platform Accessibility

Allows users to access and view data visualizations on different devices and platforms such as desktops, tablets, and smartphones.

Data Analytics Integration

Integrates with data analytics tools and platforms to perform advanced data analysis, derive insights, and enhance visualization capabilities.

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Dremio

Overview

What is Dremio?