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Firebolt Team
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Introducing Geospatial Analytics in Firebolt: Powering Location Intelligence at Scale

Announcing the public preview of Firebolt's Geospatial Analytics, bringing low-latency, spatial data processing to CDW.

Tara Shankar Jana

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Firebolt Team

Recap - Firebolt Forward: Data Warehousing in the Age of AI

Legacy data warehouses can’t handle AI apps. Firebolt is built for subsecond latency, massive concurrency, and more...

Firebolt Team

How to Boost Query Performance with Apache Iceberg in Cloud Data Warehouses

Speed up queries with Apache Iceberg and Firebolt's lightning-fast execution.

Firebolt Team

Revolutionizing Data Governance with DataStrato’s Unified Open Source Approach

Uncover the future of data governance and explore innovative solutions for a unified data ecosystem with Lisa Cao, Produ

Firebolt Team

Beyond Database Optimization with AI

Discover groundbreaking, innovative approach to database technology as you tune in to this episode with CEO DucksDB Labs

Firebolt Team

Firebolt Unleashed: High Efficiency and Low-Cost Concurrency in Action

Explore Firebolt's cost efficiency with real-world data benchmarks highlighting low latency and high concurrency.

Hiren Patel

AI in Cloud Data Warehousing

AI-driven cloud data warehousing enables faster, more accurate analytics.

Monica Cisneros

Low Latency Incremental Ingestion: Benchmarking Fast and Efficient DML Operations

Discover Firebolt's efficiency in incremental ingestion and DML workloads

Phil Simko

High Volume Ingestion: Scalable and Cost-Effective Data Loading

Explore Firebolt's bulk ingestion benchmarks, highlighting speed, cost-efficiency, and performance.

Phil Simko

The Process of Running FireScale Benchmarks

Learn about the methodology behind constructing and running the FireScale benchmarks.

Cole Bowden

Introducing FireScale - A Benchmark for High Performance and High Concurrency Analytics Workloads

FireScale reveals Firebolt’s 8x-90x price-performance edge & near-linear concurrency scaling for next-gen analytics.

Manish Agarwal

Why Choose Apache Iceberg Over Traditional Table Formats?

Learn how Apache Iceberg outperforms Hive and Delta Lake.

Firebolt Team

Robust and efficient geospatial operations using snap rounding (Part III)

We will explore in more detail how Firebolt implements robust operations on geospatial data.

Firebolt Team

How Similarweb Serves 100s of TBs to Worldwide Users in Milliseconds

At SimilarWeb, we analyze internet traffic on a global scale, empowering clients with actionable insights.

Firebolt Team

How AI is Transforming ETL in Data Warehousing

AI is automating ETL, making data processing faster, more accurate, and cost-effective.

Firebolt Team

Introducing Firebolt Editions and Compute Family Choices

Choose the right edition and compute family to optimize query performance and cost-efficiency with Firebolt.

Manish Agarwal

Cloud Data Warehouse vs. Data Lake: Which One Should You Choose?

Compare cloud data warehouses and data lakes and learn the key differences and how to make the right choice.

Firebolt Team

Under the Hood of Firebolt Compute Families

Dive into why Firebolt introduced a new compute family and when you'd want to use it.

Cole Bowden

Cloud Data Warehouse vs. Traditional Data Warehousing: Why the Shift?

Discover why businesses are migrating from traditional to cloud data warehouses.

Firebolt Team

Cloud Data Warehouse Best Practices: Tips for Maximizing Performance

Learn proven techniques to optimize cloud data warehouse performance.

Firebolt Team

Firebolt February Release Roundup: Versions 4.12 to 4.14 -> Faster queries, RBAC upgrades, and geospatial boosts

Recap of the three most recent releases in Firebolt, including changes from versions 4.12, 4.13, and 4.14.

Cole Bowden

Building Geospatial Support in Firebolt (Part-I)

This blog post explores how Firebolt implements geospatial support under the hood.

Demian Hespe

AI and Data Movement: Trends and Best Practices with Estuary’s Daniel Pálma

Transform data engineering, marketing, real-time data integration and the use of AI with Daniel Pálma’s expert insights.

Firebolt Team

Architecture and Internal Representation of the GEOGRAPHY Data Type (Part II)

Discover how Firebolt structures & optimizes GEOGRAPHY data with S2 cells, shape indexes, and pruning for fast queries.

Demian Hespe

Cloud Data Warehouse Solutions for Big Data Analytics

Discover the best cloud data warehouse solutions for big data analytics. Learn about features, & benefits.

Firebolt Team

Advanced SQL Query Techniques for Data Engineers

Advanced SQL techniques for improving query efficiency and system performance.

Firebolt Team

Firebolt Welcomes Former Oracle and Confluent Leader Hemanth Vedagarbha as President, Overseeing Global Go-To-Market Expansion and Customer-Facing Operations

Firebolt names Hemanth Vedagarbha as President to lead global GTM expansion and scale its AI-powered data warehouse.

Firebolt Team

ETL Best Practices for Data Engineers

Discover top ETL best practices for data engineers to optimize workflows, improve performance, and ensure data accuracy.

Firebolt Team

Firebolt Features: Effortless Metadata Management For Faster Workflows

Learn how Firebolt streamlines metadata management with zero-copy cloning, dynamic schema evolution for faster workflows

Jonathan Thein

Big Data Challenges & How to Overcome Them

Discover the top big data challenges and learn practical solutions to overcome them.

Firebolt Team

Primary Indexes in Firebolt: A Comprehensive Guide to Understanding, Managing, and Selecting

Discover how Firebolt's primary index optimizes data handling for large-scale analytics, enhancing query performance.

Hiren Patel

Introducing Firebolt’s Next-Generation Cloud Data Warehouse

This blog is a GA announcement of Firebolt’s next-gen cloud data warehouse that delivers low-latency analytics at scale.

Tara Shankar Jana

Firebolt’s zero-copy clone

Firebolt’s Zero-Copy Clone Feature: A cost-efficient way to clone massive tables instantly without duplicating data.

Gil Cizer

Firebolt Trial For 30 Days With $200 Free Credits — Now Open to All

Firebolt now welcomes sign-ups with personal email addresses. Explore Firebolt’s low-latency, high-concurrency CDW.

Jonathan Thein

From MySQL Bottlenecks to Firebolt Power: 28X Faster Analytics at Lower Cost

Vrio's CTO explores how Firebolt reduced ecommerce analytics latency from minutes to milliseconds, while reducing TCO.

Ryan McWilliams

Firebolt December Release Roundup: Versions 4.9 to 4.11 → Geospatial data, zero-copy cloning, and metadata operations

Firebolt delivers zero-copy cloning, a preview for processing geospatial data, and more this month.

Cole Bowden

Building Customer Trust: A CISO's Perspective on Security and Privacy at Firebolt

Firebolt's commitment to robust security measures from day one ensures that every customer's data is protected.

Nir Yizhak

AI and Data Change Management with Chad Sanderson, CEO Gable AI

In this episode of The Data Engineering Show, Chad Sanderson explores the world of data change management.

Firebolt Team

ELT with Firebolt using dbt

Deliver efficient ELT with the combination of Firebolt's elastic infrastructure and the simplicity of SQL models on dbt.

Connor Carreras

Mosha Pasumansky talks query subresult reuse at CMU

Mosha explained how Firebolt boosts query performance through query subresult caching and reuse techniques.

Cole Bowden

Data Rewind: Conversation Highlights from Zach, Matthew, Joe, and Krishnan

This is a special episode of The Data Engineering Show revisiting the best bits from three different fascinating episode

Firebolt Team

Fuzzing Firebolt: Catching 0-days as fast as our query processor

In this blog, we’ll highlight how we fuzz Firebolt’s blazing-fast query processor written in modern C++

Abhishek Sen

How we built Firebolt

This blog describes our thinking and guiding principles behind design choices while building Firebolt.

Mosha Pasumansky

Caching & Reuse of Subresults across Queries

Deep dive into how Firebolt optimizes query performance through caching and reusing results of parts of the query plan.

Alex Hall

Making a Query Engine Postgres Compliant Part I - Functions

Technical deep dive on how Firebolt evolved into a PostgreSQL-compliant database system.

Benjamin Wagner

5 Reasons to Use Firebolt

Firebolt delivers lightning-fast analytics with SQL simplicity, cost-effective performance, and high query throughput.

Cole Bowden

Tech Stacks and Tradeoffs: Xudo's Founder on Picking the Right Tools for BI Success

Wouter Trappers shares his slightly unconventional path from philosopher to data consultant and engineer.

Firebolt Team

Vector Databases Won’t Replace SQL - Andy Pavlo

Andy Pavlo, Associate Professor at Carnegie Mellon University, delves into database internals and optimization.

Firebolt Team

Firebolt DB Release Roundup: Release versions 4.6 to 4.8-> New Functions, Friendlier SQL, and Enhanced Performance

Firebolt DB Release Roundup: Release versions 4.6, 4.7 and 4.8

Tara Shankar Jana

Firebolt is Now Available in Asia Pacific (Singapore)

We're excited to announce that Firebolt is now available in the Asia Pacific (Singapore) region.

Manish Agarwal

Data Management Lifecycle in Firebolt

Learn how the data management lifecycle looks like in Firebolt

Igor Stanko

Firebolt is Now Available in EU-WEST-1

We're excited to announce that Firebolt is now available in the EU-WEST-1 region.

Krishna Thotapalli

The Resurgence of SQL: Insights from Ryanne Dolan from LinkedIn

In The Data Engineering Show, Ryanne Dolan from LinkedIn joins the Bros to discuss LinkedIn's Hoptimator project.

Firebolt Team

How we serve data from millions of gaming channels to 50K customers using Firebolt

Read on to find out how Lurkit is using Firebolt over AWS to serve advanced gaming analytics.

Tom Niskanen

Engines: Online Scaling and Upgrades

Uncover Firebolt’s Engine internals featuring zero-downtime upgrades, multi-dimensional elasticity, and granular scaling

Artem Grachev

Right size your engines and achieve unparalleled price-performance with firebolt’s granular scaling

Scale one node at a time to adjust compute resources incrementally, ensuring an ideal price-performance ratio.

Krishna Thotapalli

Announcing Firebolt Engines: Next-Generation Compute Infrastructure for Cloud Data Warehousing

Firebolt Inc., a cloud data warehouse provider, announced its next-generation compute infrastructure, Engines.

Krishna Thotapalli

How ZoomInfo transitioned from data graveyards to ROI-driven data projects

Too often expensive resources and manhours are spent on dashboards no one uses, resulting in zero ROI.

Firebolt Team

Matthew Weingarten from Disney Streaming about Data Quality Best Practices

Principles essential for data quality, cost optimization, and data modeling, as adopted by the world's leading companies

Firebolt Team

Joseph Machado, Senior Data Engineer at LinkedIn talks best practices

Data engineering should be less about the stack and more about best practices.

Firebolt Team

Professors Joe Hellerstein and Joseph Gonzalez on LLMs

Joe Hellerstein and Joseph Gonzalez inspired generations of database enthusiasts and are now on the show

Firebolt Team

Megan Lieu on powerful notebooks that enable collaboration

Megan Lieu about her approach to data advocacy as well as the power of notebooks

Firebolt Team

Transitioning from software engineering to data engineering

Every data team should have at least one data engineer with a software engineering background.

Firebolt Team

The key is in the key.

One of the more common and costly mistakes in the many data implementations is confusion about keys.

Robert Harmon

Simplifying time variance in a SQL data warehouse

An issue many coming into the data warehouse world is difficulty with is managing time variance at scale and efficiency.

Robert Harmon

"Do data architects exist anymore?"

"Do data architects exist anymore?" Wow, as a recovering data architect that's a loaded question.

Robert Harmon

Who's down with OBT? I can assure you, not me.

I'm not a fan of dimensional modeling. It exists to solve physical problems, not logical problems.

Robert Harmon

Rob's high performance data warehousing rule #4: Delete nothing, update only metadata.

Rob says: delete nothing, update only metadata.

Robert Harmon

Vin Vashishta explains why we should stop using dashboards

Vin Vashishta, the guy we all love to follow, has never seen a dashboard with positive ROI.

Firebolt Team

Rob's high performance data warehousing rule #3: Strong operational data store ensures high performance

This has nothing to do with the DW itself. But if you miss it, you'll fail with your warehouse project.

Robert Harmon

Rob's high performance data warehousing rule #2: There's no point in measuring anything, if the data team can't measure itself.

"There's no point in measuring anything, if the data team can't measure itself."

Robert Harmon

Rob's high performance data warehousing rule #1: if you cannot constrain a thing, you cannot ingest that thing.

"If you cannot constrain a thing, you cannot ingest that thing."

Robert Harmon

Joe Reis and Matt Housley on the fundamentals of data engineering

Joe Reis and Matt Housley joined the bros for some much-needed ranting, priceless data advice, and good laughs.

Firebolt Team

How IQVIA Maximizes Analytics Performance for Healthcare

IQVIA deep dive into maximizing impact of BI solutions for faster and more informed decision-making in healthcare.

Firebolt Team

Large scale data engineering at Momentive.ai - Meenal Iyer

Meenal Iyer, VP Data at Momentive.ai, talks about enforcing collaboration in large organizations

Firebolt Team

Data engineering from the early 2000s till today - BlackRock

When it comes to data management, have we come a long way since the early 2000s?

Firebolt Team

Bill Inmon, the Godfather of Data Warehousing

As people in the data industry go, Bill Inmon is among the top, often seen as the godfather of the data warehouse.

Firebolt Team

Data quality with ‘dbt’ and Firebolt

dbt data quality - Implementing data quality tests and using dbt extensions for enhanced data quality checks.

Robert Harmon

A primer on analyzing semi-structured data

This guide will provide you with the fundamental knowledge necessary to handle semi-structured data effectively. 

Firebolt Team

Zach Wilson on what makes a great data engineer

How good you are at Spark or Flink ≠ how good you are at data engineering. Zach Wilson explains.

Firebolt Team

How ZipRecruiter and Yotpo power self-service data platforms that work

How ZipRecruiter and Yotpo build resilient self-service products that keep customers happy and engineers calm

Firebolt Team

25 Ad Tech Data Pros: Workshop Summary

In a recent workshop, 25 data pros working in the Ad Tech industry discussed querying large data sets efficiently

Matthew Darwin

How we mastered dbt: A true story

At Firebolt, we found out that a duet of dbt and Paradime works for our needs.

Olga Braginskaya

Data Observability with Millions of Users - Barr Moses

Barr Moses explains how to make sure your data is accurate in a world where so many different teams are accessing it

Firebolt Team

AWS re:Invent Keynote Recap for Data Professionals

AWS re:invent 2022 was all about building the anticipation and delivering on expectations of us technologists. 

Firebolt Team

Analyzing the GitHub Events Dataset using Firebolt - Incremental Updates with Apache Airflow

Looking at GithubArchive dataset of public events - leveraging Apache Airflow workflows for keeping our data up-to-date.

Alexander Reelsen

Analyzing the GitHub Events Dataset using Firebolt - Writing a Data App using Java

Writing a small data app using the Firebolt JDBC drive.

Alexander Reelsen

Analyzing the GitHub Events Dataset using Firebolt - Querying with Streamlit

Writing a data app, using Streamlit and Jupyter and the Firebolt Python SDK. A multi-series blog.

Alexander Reelsen

Analyzing the GitHub Events Dataset using Firebolt - Using Jupyter for data exploration

In this blog we will discover the data using Streamlit and Jupyter and the Firebolt Python SDK.

Alexander Reelsen

What is a Data App?

Data apps are applications that rely heavily on data and have an easy to use.

Firebolt Academy

Event streams in Firebolt

Event streams have always been problematic to analyze in SQL. This is how we do it.

Robert Harmon

How To Support Ad Hoc Analysis - Part 1

How to support ad hoc analysis: Part 1 - The 4 requirements for an ad hoc analytics architecture

Robert Meyer

Firebolt and Data Mesh

Data Mesh is hot stuff. But from a technology perspective it’s still not very well defined.

Matthew Darwin

Hey David and Tristan, this is where Firebolt is at

"When I see David Jayatillake and Tristan Handy comment on Firebolt's approach it is clear that Firebolt is on track."

Robert Harmon

Big Data Analytics for Gaming

In our recent ‘Big Data Analytics for Gaming Workshop’ we let the audience do the talking, here’s a summary of the talk.

Firebolt Team

How To Support Ad Hoc Analysis - Part 2

How to support ad hoc analysis - Part 2: The right ad hoc analytics architecture

Robert Meyer

Semi-structured data modeling

How to ingest, store and query JSON data, for example, is a consistent question on the minds of customers.

Firebolt Team

PostgreSQL Swiss army knife and The analytics workload

Is Postgres truly the right engine for analytics? 

Firebolt Team

Making Observability a Key Business Driver

80% of the code that you write doesn’t work on the first try. But knowing which 80% is not working is the real challenge

Firebolt Team
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