Discover the new LOCATION object, a foundational improvement to Firebolt’s data access model.
The Future of Data Processing: PostgreSQL Evolution with YingJun Wu of PingCAP.
Learn how GROUPING SETS work and how Firebolt’s implementation uses smart query planning to execute them efficiently.
Discover how Firebolt implements SQL functions for data exploration.
Supercharge your data workflows by connecting Firebolt to AI tools with the new MCP Server.
Legacy BI tools can’t keep up with AI. Firebolt Forward revealed 5 trends defining the future.
Explore how Firebolt transaction manager works
Uncover the future of data governance and explore innovative solutions for a unified data ecosystem with Lisa Cao, Produ
Discover groundbreaking, innovative approach to database technology as you tune in to this episode with CEO DucksDB Labs
Learn about the methodology behind constructing and running the FireScale benchmarks.
FireScale reveals Firebolt’s 8x-90x price-performance edge & near-linear concurrency scaling for next-gen analytics.
Dive into why Firebolt introduced a new compute family and when you'd want to use it.
Choose the right edition and compute family to optimize query performance and cost-efficiency with Firebolt.
We will explore in more detail how Firebolt implements robust operations on geospatial data.
Recap of the three most recent releases in Firebolt, including changes from versions 4.12, 4.13, and 4.14.
Transform data engineering, marketing, real-time data integration and the use of AI with Daniel Pálma’s expert insights.
Discover how Firebolt structures & optimizes GEOGRAPHY data with S2 cells, shape indexes, and pruning for fast queries.
This blog post explores how Firebolt implements geospatial support under the hood.
Announcing the public preview of Firebolt's Geospatial Analytics, bringing low-latency, spatial data processing to CDW.
Firebolt names Hemanth Vedagarbha as President to lead global GTM expansion and scale its AI-powered data warehouse.
Firebolt’s Zero-Copy Clone Feature: A cost-efficient way to clone massive tables instantly without duplicating data.
Firebolt now welcomes sign-ups with personal email addresses. Explore Firebolt’s low-latency, high-concurrency CDW.
In this episode of The Data Engineering Show, Chad Sanderson explores the world of data change management.
Vrio's CTO explores how Firebolt reduced ecommerce analytics latency from minutes to milliseconds, while reducing TCO.
Learn how Firebolt streamlines metadata management with zero-copy cloning, dynamic schema evolution for faster workflows
Firebolt delivers zero-copy cloning, a preview for processing geospatial data, and more this month.
Wouter Trappers shares his slightly unconventional path from philosopher to data consultant and engineer.
Firebolt DB Release Roundup: Release versions 4.6, 4.7 and 4.8
We're excited to announce that Firebolt is now available in the Asia Pacific (Singapore) region.
Firebolt delivers lightning-fast analytics with SQL simplicity, cost-effective performance, and high query throughput.
Mosha explained how Firebolt boosts query performance through query subresult caching and reuse techniques.
This is a special episode of The Data Engineering Show revisiting the best bits from three different fascinating episode
Firebolt's commitment to robust security measures from day one ensures that every customer's data is protected.
We're excited to announce that Firebolt is now available in the EU-WEST-1 region.
In The Data Engineering Show, Ryanne Dolan from LinkedIn joins the Bros to discuss LinkedIn's Hoptimator project.
In this blog, we’ll highlight how we fuzz Firebolt’s blazing-fast query processor written in modern C++
Discover how Firebolt's primary index optimizes data handling for large-scale analytics, enhancing query performance.
Deliver efficient ELT with the combination of Firebolt's elastic infrastructure and the simplicity of SQL models on dbt.
Discover Firebolt's efficiency in incremental ingestion and DML workloads
Explore Firebolt's bulk ingestion benchmarks, highlighting speed, cost-efficiency, and performance.
Explore Firebolt's cost efficiency with real-world data benchmarks highlighting low latency and high concurrency.
This blog describes our thinking and guiding principles behind design choices while building Firebolt.
This blog is a GA announcement of Firebolt’s next-gen cloud data warehouse that delivers low-latency analytics at scale.
Deep dive into how Firebolt optimizes query performance through caching and reusing results of parts of the query plan.
Technical deep dive on how Firebolt evolved into a PostgreSQL-compliant database system.
Read on to find out how Lurkit is using Firebolt over AWS to serve advanced gaming analytics
Uncover Firebolt’s Engine internals featuring zero-downtime upgrades, multi-dimensional elasticity, and granular scaling
Scale one node at a time to adjust compute resources incrementally, ensuring an ideal price-performance ratio.
Firebolt Inc., a cloud data warehouse provider, announced its next-generation compute infrastructure, Engines.
Andy Pavlo, Associate Professor at Carnegie Mellon University, delves into database internals and optimization.
Too often expensive resources and manhours are spent on dashboards no one uses, resulting in zero ROI.
Principles essential for data quality, cost optimization, and data modeling, as adopted by the world's leading companies
Data engineering should be less about the stack and more about best practices.
Joe Hellerstein and Joseph Gonzalez inspired generations of database enthusiasts and are now on the show
Megan Lieu about her approach to data advocacy as well as the power of notebooks
Every data team should have at least one data engineer with a software engineering background.
One of the more common and costly mistakes in the many data implementations is confusion about keys.
An issue many coming into the data warehouse world is difficulty with is managing time variance at scale and efficiency.
"Do data architects exist anymore?" Wow, as a recovering data architect that's a loaded question.
I'm not a fan of dimensional modeling. It exists to solve physical problems, not logical problems.
Rob says: delete nothing, update only metadata.
Vin Vashishta, the guy we all love to follow, has never seen a dashboard with positive ROI.
This has nothing to do with the DW itself. But if you miss it, you'll fail with your warehouse project.
"There's no point in measuring anything, if the data team can't measure itself."
"If you cannot constrain a thing, you cannot ingest that thing."
Joe Reis and Matt Housley joined the bros for some much-needed ranting, priceless data advice, and good laughs.
IQVIA deep dive into maximizing impact of BI solutions for faster and more informed decision-making in healthcare.
As people in the data industry go, Bill Inmon is among the top, often seen as the godfather of the data warehouse.
Meenal Iyer, VP Data at Momentive.ai, talks about enforcing collaboration in large organizations
When it comes to data management, have we come a long way since the early 2000s?
Learn how the data management lifecycle looks like in Firebolt
This guide will provide you with the fundamental knowledge necessary to handle semi-structured data effectively.
In this blog, we focus on distributed query execution as an integral part of Firebolt.
How good you are at Spark or Flink ≠ how good you are at data engineering. Zach Wilson explains.
dbt data quality - Implementing data quality tests and using dbt extensions for enhanced data quality checks.
How ZipRecruiter and Yotpo build resilient self-service products that keep customers happy and engineers calm
In a recent workshop, 25 data pros working in the Ad Tech industry discussed querying large data sets efficiently
At Firebolt, we found out that a duet of dbt and Paradime works for our needs.
Barr Moses explains how to make sure your data is accurate in a world where so many different teams are accessing it
Writing a small data app using the Firebolt JDBC drive.
Looking at GithubArchive dataset of public events - leveraging Apache Airflow workflows for keeping our data up-to-date.
In this blog we will discover the data using Streamlit and Jupyter and the Firebolt Python SDK.
Writing a data app, using Streamlit and Jupyter and the Firebolt Python SDK. A multi-series blog.
Event streams have always been problematic to analyze in SQL. This is how we do it.
Amplitude's cutting-edge data stack and how it processes 5 Trillion real-time events while dealing with mutable data
Data apps are applications that rely heavily on data and have an easy to use.
AWS re:invent 2022 was all about building the anticipation and delivering on expectations of us technologists.
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
How to ingest, store and query JSON data, for example, is a consistent question on the minds of customers.
Is Postgres truly the right engine for analytics?
Data Mesh is hot stuff. But from a technology perspective it’s still not very well defined.
In our recent ‘Big Data Analytics for Gaming Workshop’ we let the audience do the talking, here’s a summary of the talk.
Sudeep Kumar, Principal Engineer at Salesforce considers the shift to Clickhouse as one of his biggest accomplishments
"When I see David Jayatillake and Tristan Handy comment on Firebolt's approach it is clear that Firebolt is on track."
Max walks the Bros through his recipe for a smart data-driven company, and the genesis of Airflow, Superset & Presto.
Firebolt provides an alternative to Druid, delivering fast response times, high concurrency and the convenience of a Saa
In this post, we look at factors to consider when building a data warehouse.
According to Yoav Shmaria, VP R&D Platform at Similarweb, the best way to manage data warehouse costs is tagging
How to Set Up Your Data Analytics Stack with Kafka, Hevo, and Firebolt.
Are you spending more than you planned on your Data Warehouse? Analyze more. Use less compute resources.
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