When we started developing the Coalesce product almost three years ago, we made a bold choice. We designed our data transformation solution to work exclusively with Snowflake.
We feel as confident in that decision today as we did when we founded our company. From Snowflake’s values and design to the benefits it offers its customers, we feel that we’ve always been aligned with the company and its innovative framework.
My co-founder, Satish Jayanthi, and I met while working at data warehouse and transformation company WhereScape. There, we witnessed the challenges that many of the largest organizations in the world faced when working with big data, and we saw time and again how legacy database and transformation products didn’t solve issues around scalability, resource constraints, data lineage, or time-consuming manual work.
Lack of innovation created a massive bottleneck in the data analytics supply chain, ultimately costing companies both capital and productivity.
Inspired by Innovation in the Data Cloud
It was at WhereScape where Satish and I were introduced to a then-new platform called Snowflake. Its advantages were clear: Snowflake was built from the ground up for the extensibility and flexibility of the cloud. Its novel multi-cluster shared data architecture–consisting of three layers: storage, compute resources, and cloud services–scaled up and down automatically and offered near limitless capacity for running concurrent queries regardless of size. It automated so many of what used to be manual database management and administration processes and tasks. Last but not least, we realized, Snowflake’s multi-cloud availability and cross-cloud potential (at the time; now it is a reality) would change our industry dramatically, and for the better.
It was also obvious that, unlike most technology startups, Snowflake’s founders had spent a significant amount of time and effort to develop a product that was so innovative and so far ahead of competitors’ products–legacy and open-source alike–that competitors could never catch up. The moat was already too wide to cross.
Snowflake’s approach inspired us to ask ourselves: What if we could design a solution for data transformations from the ground up, that solved the biggest challenges in the field much in the same way Snowflake solved some of the biggest challenges in data warehousing (and consequently expanded to fields like data science and application development)–all while taking advantage of all that Snowflake had to offer?
In our experience, Snowflake was the best data platform on the market, and Coalesce aimed to offer the best data transformation solution for its users.
Focus on Automation-Enabled Efficiency, Extensibility, Flexibility
What makes Snowflake so exceptional in the data and analytics landscape are a few core tenets of the platform that align completely with the goals we set for Coalesce: its simplicity, ease of use and intuitive design, and the automation-enabled efficiency it provides across multiple data and analytics workloads.
Automation is a crucial aspect of all best-of-breed technologies.
Snowflake’s speed and agility are the result of proprietary automations that ultimately improve time-to-value for data. These automations are bolstered by other technologies from its partner network, such as Fivetran for data ingestion and Sigma for business intelligence and reporting. Even with these innovative tools, however, data engineers still spend significant time on data transformations—an area where automation has historically lagged.
The proliferation in recent years of code-first, open-source technologies may have enabled small or midsize organizations to modernize the transformation part of their data stack, but those solutions don’t scale. More importantly, we believe that organizations that choose open-source billed as “free” ultimately foot a much larger bill in the form of higher TCO hidden in the gross amount of cost associated with the labor to get those solutions to properly function. Like Snowflake’s founders and product leaders, we believe that organizations should “choose open wisely.”
With all that in mind, we wanted to focus on a solution that offers full extensibility and flexibility where it matters, while prioritizing simplicity and ease of use so users can get to value as quickly as possible.
With flexible and efficient enterprise-scale data transformations on top of an already best-in-class platform like Snowflake, the development and analytics landscape would radically improve.
In Lockstep with New Features and Capabilities
Our commitment to developing solutions within and alongside Snowflake supports a better development experience while capturing its benefits. Snowflake sets an unmatched pace of innovation. Since the Coalesce team is hyper-focused on optimizing for Snowflake alone, our product matches Snowflake’s rate of innovation, which stays well ahead of industry standards.
For example, when Snowflake released Dynamic Tables (in private preview as of November 2022), our team had already developed support for them. This seamless forward momentum contributes to productivity for our clients, so their data teams can tackle delivering insights, not troubleshooting or developing manual processes to take advantage of new features.
When an enterprise makes the decision to partner with Snowflake, it is investing in the overall philosophy that drives the platform. The same goes for us. We have long held the same principles as Snowflake—ease of use, simplicity, intuitive design, and speed—and that alignment remains important to us not just as developers, but as people.
Are we committing Snowflake exclusively, forever? What about other platforms? We get those questions a lot; from Snowflake’s competitors, and from our own competitors. To say that we’ll focus on Snowflake exclusively forever would be irresponsible, knowing that there could come a time when Snowflake could compete with us directly. That said, Coalesce is committed to supporting Snowflake in the foreseeable future as its platform expands into OLTP with Unistore, data science with Snowpark, and more.
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