Hello data world!
So we’ve all heard that “data is the new oil” way too many times. It’s been said so often that I personally feel slightly nauseous every time someone says that (sorry). But, the reality is that companies in every sector were already amassing as much data as they could even pre-COVID-19. Add to that today’s accelerated digital transformation we’re experiencing in every part of our lives due to COVID-19 and we’re talking about very significant data growth rates.
That’s great — plenty of oil for everyone. Right?
Well, not so fast.
While we can confidently say that humanity has pretty much solved the storage aspect of big data, it seems that we’re still stuck with less-than-advanced processes of refining this data into insights. Imagine sitting in front of a huge pile of crude oil nicely stored in barrels, with nothing but cocktail straws to extract that oil.
In the best case scenario, turning big data into insights today is either painfully slow, expensive, or labor intensive. And in the worst case scenario — all of the above.
Ironically, everyone brags about having big data as soon as they have multiple terabytes or petabytes of data in storage. But, due to the difficulties in analyzing this data, most organizations only analyze a fraction of that big data. That’s a fact that is usually overlooked. This isn’t quite the “big data analytics” dream everyone had in mind.
Storing big data is very different than analyzing big data. And what’s the point in having big data if you can’t analyze it after all?
Companies are often forced to make data compromises in order to achieve only a fraction of the business value the data really holds. They’re forced to look at narrow time windows, at aggregated data and frequently, they also find themselves looking at stale data that doesn’t even reflect the current state of their business.
Add to that the substantial work and resources that go into building and scaling those data pipelines and it’s easy to understand the frustration that so many companies experience.
I’ve spent my entire life in and around data analytics.
In 2004, I founded a successful business intelligence (BI) company called Sisense, which focuses on data integration and visualization for complex data challenges and today, serves thousands of customers globally.
Over the years, I’ve seen the data analytics space evolve rapidly and a few years ago, I realized that Hadoop is dead, and that the data warehouse will be making a big comeback. I decided it was time for me to go deeper in the data stack to tackle some of the massive data challenges the world was about to face.
That’s how Firebolt came to life.
Firebolt is a complete redesign of the data warehouse for the era of the cloud and data lakes. Our aim is to enable organizations to deliver an incredible data analytics experience regardless of the size and usage patterns of a company’s data without having to constantly be worried about performance and costs.
Not just another cloud data warehouse
You must be saying to yourself, there’s so many data warehouses out there, who the hell needs another one?
Well, that’s an excellent point.
So without further ado, here are the three main things that make Firebolt unique and a few reasons why some of the world’s most advanced tech companies are partnering with us:
- Speed @ scale — Firebolt was built from the ground up with fanatical attention to how each step in the data journey, from storage to the compute layer CPU, can be optimized. We set out to build the most powerful data warehouse available but also the most efficient one when it comes to how it utilizes cloud resources. The brute force approach of throwing more compute and money at the problem is limited and can only take you so far (unless you feel comfortable wearing a 6XL T-shirt :) ). Firebolt leverages the elasticity of the cloud combined with the infinite scale it provides to deliver extreme query speed @ scale that no other solution offers.
- Rapid warehousing — data teams today spend too much time on pre-aggregation ETLs, flattening semi-structured data, cluster management, as well as other “fun” tasks like vacuuming, reclustering, partitioning and the list goes on and on. No more! At Firebolt we believe that data warehouses should be much easier to use and should do all that for you. That’s why we focus on turning everything that used to be complicated and labor intensive into simple tasks. This is how rapid warehousing is achieved and it’s how you replace time spent on non productive tasks with valuable data analysis and development.
- Best price-performance ratio in the industry — with the common “pay-per-use” model, cloud data warehouse vendors earn more if your queries take longer to run. That’s a major conflict of interest that no one seems to be talking about! (I like to call it the elephant in the warehouse). Cloud data warehouse providers essentially have no financial incentive to improve their query speed or reduce your cost per hour, as it will directly impact their revenues. At Firebolt we decided to introduce a new pricing model that is fair, transparent, and allows you to scale without breaking the bank, whereby you pay just the AWS base cost for the cloud resources you consume, and not a penny more. In addition, Firebolt charges a fixed annual subscription for the services we provide that is based on the size of your data set. Our innovative business model saves our customers up to 90% of their cloud data warehouse bill and ensures true alignment of interests. Our customers can rely on Firebolt to continue to roll out optimizations resulting in reduced cloud costs and improved query performance.
So if you have to sum it up, Firebolt is a cloud native data warehouse that is faster, easier to use and offers an unparalleled price-performance ratio.
Data teams today are faced with immense challenges. We’ve made it our mission at Firebolt to transform the way the world processes data.
We envision a world where big data is lightning fast!
How fast? I welcome you to sign up and see Firebolt in action on your own data.
EldadCEO / Co-FounderFirebolt
P.S. I would love to hear your thoughts