Why Alvin?
You're in control
What differentiates our approach in the metadata space is that apart from a set of powerful tools and automations that cater to common data workflows, we also make the metadataset available for our users at their fingertips.
It comes from our understanding that every data environment, priorities and setup is too unique to be served by a one-size-fits-all solution.
This is both a way for virtually any metadata insight to be derived by anyone with an understanding of SQL, but also an escape hatch for the user to dive in and customize anything that needs to be tweaked just a little bit. We all know the feeling!
It just works
We have been expanding our technical approach to processing APIs, SQL and metadata at scale dealing for a long time, in multiple data environments and dialects. Behind Alvin stands a continuously evolving and robust test base and, before all, a team of experts in the space with true passion for the challenges that come with building a tool like ours.
Read up on our piece covering the technology and philosophy behind the tech: https://www.alvin.ai/posts/compilers-the-answer-to-fully-automated-data-lineage
The parsing itself is based on a novel approach that is superior to solutions like parser generators (ie ANTLR) in both performance and extensibility.
Richest data model
Our full statement parser outrivaled the market not only by accuracy measured in covered query types, but also by the contextualisation designed with the needs of growth-minded, agile data teams in mind.
Cloud-native
We grew from and evolve with the Modern Data Stack. This means the features and workflows around it answer to the modern data team. Alvin is your ally in navigating dbt-led democratization, data debt, the challenges of Analytics Engineering or Data Science-ready pipelines – all the good, the bad and the ugly that comes with the growth mindset we see and support in the space.
Turnkey
It takes a few minutes to set up credentials. Simple as that 🤷♀️
Cheaper than open source
There are open source solutions and projects that claim to do lineage, but they either don't have the breadth of statement coverage or they simply dont work at scale (python based). This goes for lineage but also dealing with APIs, rate limits, retries and cost-efficient data processing is often the last 5% of the work that takes 95% of the time.
The time you will spend debugging, issuing PRs and doing manual hacks (or adapting your SQL to work with the open source parsers), in addition to the infrastructure maintenance and hosting time / costs is quickly recouped with Alvin.
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