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.
How to enable sub-second analysis across billions of rows of customer behavior data: Part I - Setting up the load
Klarna is one of the leading fintech companies in the world, valued at $45B.
An episode about Eventbrite’s data stack modernization process, and how you get engineers to adopt new technologies
One of the ways Firebolt is able to support data-driven applications is by leveraging aggregating indexes on the tables.
How the data platform evolved as Slack grew from a startup to an IPOed and then acquired company.
Should data engineering AND BI be handled by the same people?
Why would you create ugly data? According to Jens Larsson, don’t even go near raw data.
Let us guide you through the process of identifying the performance bottlenecks in your query in just 5 simple steps.
Ananth Packkildurai is Principal Software Engineer at Zendesk and runs one of the strongest newsletters in data
The data warehousing market has gone absolutely mad over performance. Why is this the case?
Many programming languages are imperative – tell the compiler how to operate by providing the instructions in order.
Demand from engineering teams has skyrocketed since Firebolt emerged from stealth last year
Gong manages hundreds of thousands of videoconferences and millions of emails PER DAY, which add up to hundreds of TBs.
Bolt engineers are in the midst of designing a new next-gen data platform
Indexes are the primary way for users to accelerate query performance in Firebolt. Learn about them here.
Scaling a data platform to support 1.5T events per day requires complicated technical migrations
Everything you needed to know about cloud data warehouses but were afraid to ask...
Learn when to use Postgres, MySQL, in-memory databases, HTAP, or data warehouses to meet the 1 sec SLA in analytics.
It’s the mother of all development projects. You use it daily. And so do 65M developers around the world.
Lear the top 10 tips of how to improve your cloud data warehouse performance.
How does a tech stack that always needs to be at the forefront of technology look like?
More and more, people are asking me “how do you compare Snowflake and Databricks?” We did our best to answer.
How Vimeo handles Data Ops to deal with massive scale?
How does Substack's data platform support 500K paying subscribers?
Steven Moy thoroughly explains Yelp’s data architecture under the hood and how it evolved over the past ten years.
Canva is one of the hottest, if not the hottest, graphic design platforms out there.
Appsflyer deals not only with 120 billion events per day, but does so while growing quickly as a company
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