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Blog

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Blog

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
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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

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

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

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

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

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

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

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

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

How we built Firebolt

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

Mosha Pasumansky

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

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

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

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

Cloud data warehouse costs: Look before you leap

In this post, we look at factors to consider when building a data warehouse.

Firebolt Team

The Creator of Airflow About His Recipe for Smart Data-Driven Companies

Max walks the Bros through his recipe for a smart data-driven company, and the genesis of Airflow, Superset & Presto.

Firebolt Team

How Similarweb Delivers Customer Facing Analytics Over 100s of TBs

According to Yoav Shmaria, VP R&D Platform at Similarweb, the best way to manage data warehouse costs is tagging

Firebolt Team

A ClickHouse Review from a Practitioner’s Point of View

Sudeep Kumar, Principal Engineer at Salesforce considers the shift to Clickhouse as one of his biggest accomplishments

Firebolt Team

Druid Architecture Compared to Firebolt - A Practitioner’s View

Firebolt provides an alternative to Druid, delivering fast response times, high concurrency and the convenience of a Saa

Ben Hopp

A new level of efficiency in analytics

Are you spending more than you planned on your Data Warehouse? Analyze more. Use less compute resources.

Boaz Farkash

Simplicity and Power of Agg Indexes at Scale

One of the ways Firebolt is able to support data-driven applications is by leveraging aggregating indexes on the tables.

David Welch

A Deep Dive into Slack's Data Architecture

How the data platform evolved as Slack grew from a startup to an IPOed and then acquired company.

Firebolt Team

How Eventbrite is Modernizing its Data Stack

An episode about Eventbrite’s data stack modernization process, and how you get engineers to adopt new technologies

Firebolt Team

Loading Snowplow data into Firebolt with dbt

How to enable sub-second analysis across billions of rows of customer behavior data: Part I - Setting up the load

Todd Beauchene

How Klarna Designed a New Data Platform in the Cloud

Klarna is one of the leading fintech companies in the world, valued at $45B.

Firebolt Team

Embedded Analytics vs Data Apps

There has been a lot of talk recently about Data Apps. That's what Firebolt is thinking about data apps.

Boaz Farkash

Faster Data Replication from Kafka Using Hevo and Firebolt

How to Set Up Your Data Analytics Stack with Kafka, Hevo, and Firebolt.

Brian Bickell

Cloud Data Warehouse Requirement Template

A checklist of criteria to help you determine which factors are most important for the success of your organization

Tamar Gal

Understanding the tech behind Snowflake’s IPO and what’s to come

The technological concepts that make Snowflake so unique, and why it has proven to be so disruptful for the data space.

Boaz Farkash

The Evolution of Data Warehouses and Query Engines on Amazon Web Services (AWS)

Choosing the right data warehouse and analytics infrastructure on Amazon Web Services (AWS) can be confusing.

Robert Meyer

Transitioning Scopely’s 5.5 PB Data Platform to the Modern Data Stack

Should data engineering AND BI be handled by the same people?

Firebolt Team

AWS Athena Error: Query exhausted resources at this scale factor

If you’re using Amazon Athena, you may have seen these errors. About AWS Athena errors and how to deal with them.

Robert Meyer

The real meaning of a data lake

Making sense of a data lakes, delta lake, lakehouse, data warehouse and more.

Robert Meyer

The Double Redshift: About Redshift Alternatives and Limits

When do you need to shift from Redshift, and what are the alternatives? Learn here.

Robert Meyer

Snowflake vs Firebolt

We often get asked “what’s the difference between Firebolt and Snowflake?” and it reminds me of Frozen.

Robert Meyer

5 steps to debug your complex SQL queries in Firebolt

Let us guide you through the process of identifying the performance bottlenecks in your query in just 5 simple steps.

Matan Sarig

Snowflake vs Databricks vs Firebolt

More and more, people are asking me “how do you compare Snowflake and Databricks?” We did our best to answer.

Robert Meyer

Athena vs. Redshift Spectrum vs. Presto

Learn some simple rules of thumb you can use to choose the best federated query engine for your company's needs.

Robert Meyer

Choosing Between The Best Federated Query Engine And a Data Warehouse

How companies should avoid creating a slow many headed federated Gorgon out of out of Athena.

Robert Meyer

Postgres and MySQL for Analytics - Meeting the 1 second SLA

Learn when to use Postgres, MySQL, in-memory databases, HTAP, or data warehouses to meet the 1 sec SLA in analytics.

Robert Meyer

Firebolt Announces Series C Round at $1.4 Billion Valuation to Build the World's Fastest and Most Versatile Cloud Data Warehouse

Demand from engineering teams has skyrocketed since Firebolt emerged from stealth last year

Firebolt Team

Druid, ClickHouse, and Pinot vs data lakes and data warehouses (2023)

How to choose the best analytics engine for each type of analytics.

Robert Meyer

Firebolt Indexes in Action (clustered and non-clustered)

Indexes are the primary way for users to accelerate query performance in Firebolt. Learn about them here.

Octavian Zarzu
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