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.
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 this blog, we’ll highlight how we fuzz Firebolt’s blazing-fast query processor written in modern C++
Discover Firebolt's efficiency in incremental ingestion and DML workloads
Deliver efficient ELT with the combination of Firebolt's elastic infrastructure and the simplicity of SQL models on dbt.
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.
Discover how Firebolt's primary index optimizes data handling for large-scale analytics, enhancing query performance.
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.
This guide will provide you with the fundamental knowledge necessary to handle semi-structured data effectively.
Uncover Firebolt’s Engine internals featuring zero-downtime upgrades, multi-dimensional elasticity, and granular scaling
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.
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.
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.
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."
IQVIA deep dive into maximizing impact of BI solutions for faster and more informed decision-making in healthcare.
Learn how the data management lifecycle looks like in Firebolt
In this blog, we focus on distributed query execution as an integral part of Firebolt.
dbt data quality - Implementing data quality tests and using dbt extensions for enhanced data quality checks.
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.
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.
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.
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.
"When I see David Jayatillake and Tristan Handy comment on Firebolt's approach it is clear that Firebolt is on track."
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.
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
One of the ways Firebolt is able to support data-driven applications is by leveraging aggregating indexes on the tables.
There has been a lot of talk recently about Data Apps. That's what Firebolt is thinking about data apps.
Let us guide you through the process of identifying the performance bottlenecks in your query in just 5 simple steps.
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
Indexes are the primary way for users to accelerate query performance in Firebolt. Learn about them here.
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.
Lear the top 10 tips of how to improve your cloud data warehouse performance.
More and more, people are asking me “how do you compare Snowflake and Databricks?” We did our best to answer.
How to choose the best analytics engine for each type of analytics.
Upstart cloud data warehouse sees rapid growth in 2021, plans to double its workforce
Amazon Athena engine version 2 - what’s new and big enough to call this a 2.0 release?
Making sense of a data lakes, delta lake, lakehouse, data warehouse and more.
Working with semi-structured data can be more like a Jason (horror movie) Sequel than JSON SQL.
Explore the significant differences between ELT and ETL data integration processes and find the best option for you.
How to accelerate Looker performance on Redshift, Snowflake and BigQuery? Short-term fixes and the long-term solutions.
When do you need to shift from Redshift, and what are the alternatives? Learn here.
Learn how to upgrade from Tableau extracts to Tableau live connection to deliver sub-seconds performance every time.
If you’re using Amazon Athena, you may have seen these errors. About AWS Athena errors and how to deal with them.
A detailed comparison of Snowflake vs. Redshift, by architecture, scalability, performance, use cases and cost.
Learn some simple rules of thumb you can use to choose the best federated query engine for your company's needs.
How companies should avoid creating a slow many headed federated Gorgon out of out of Athena.
A checklist of criteria to help you determine which factors are most important for the success of your organization
Why even simple queries can be slow in cloud data warehouses and how Firebolt uses indexing to prune data and stay fast?
How to support ad hoc analysis - Part 2: The right ad hoc analytics architecture
How to support ad hoc analysis: Part 1 - The 4 requirements for an ad hoc analytics architecture
"In the beginning, there was a data mess". Don’t Panic, just read our data hitchhiker’s guide to cloud analytics.
The funding included participation from Zeev Ventures, TLV Partners, Bessemer Venture Partners and Angular Ventures.
We often get asked “what’s the difference between Firebolt and Snowflake?” and it reminds me of Frozen.
Choosing the right data warehouse and analytics infrastructure on Amazon Web Services (AWS) can be confusing.
There’s so many data warehouses out there, who the hell needs another one? Three main things that make Firebolt unique.
The technological concepts that make Snowflake so unique, and why it has proven to be so disruptful for the data space.
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