You can quickly become enamored with graph databases. When you discover that a short graph query can express what took you 6 weeks and 2 ounces of midnight oil in SQL - it is a life changing experience. When you use those queries to gain new insights about your customers through graph analytics, it is transformational for your business. So what happens when the technology you’ve so fallen in love with and become so reliant on, grinds to a halt? Imagine what that could do to your business. 2018 was widely hailed in the industry to be the year of graph databases. The sheer breadth of use cases for graph databases was (and still is) endless and it seemed like graphs would be ubiquitous in enterprise data pipelines. Four years later, have graph databases fulfilled that promise? Are graph databases truly a ubiquitous element in enterprise tech stacks today? If you’ve explored any of the popular graph databases out there, you’ve probably reached the same conclusion that we have - a resounding NO! The simplicity and intuitiveness of the graph data model makes it a dream for data scientists and developers alike. So why haven’t graphs revolutionized the database industry yet? It turns out that an inability to provide predictably high performance at scale is the nemesis of graph databases. This is especially true in the enterprise world, where scale is not a buzzword, but really matters. When you’re serving millions of customers across the globe, 24x7 - predictable performance at scale is crucial for the sustained growth of your application, and your business. There’s only limited value you can extract from a graph database that only works well on small datasets. The true value of a graph database lies in the ability to harness this technology at massive scales. When you can gain insights from deep and intricate relationships across your entire dataset, without sacrificing performance, it can give you the legs to leapfrog your competition. It's easy to be confused by marketing jargon when it comes to scale. By 'scale' we mean graphs that are terabytes to petabytes in size, spanning tens of billions of vertices and hundreds of billions of edges. In simpler words, a graph large enough that it needs a distributed cluster to store it, and cannot fit in-memory on a single machine. Most of the popular graph database vendors today have adopted read-replica architectures, which are simply not engineered to handle large volumes of data. Performance craters as soon as your dataset grows beyond the memory capacity of a single instance, leaving the database practically unusable for your application. At Aerospike, our core database technology solves these problems and enables our customers to harness the power of the graph data model. Aerospike has been built as a globally distributed database from the ground up. Using a Hybrid Memory Architecture™, Aerospike Database provides predictable low latency, for strong consistency and high availability modes. Our technology is proven to perform sub-millisecond queries at Petabyte scale while reducing the server footprint at the same time. Our customers have been clamoring for us to combine the well known benefits of Aerospike as a datastore with the elegance of the graph data model. Over the last few months, we’ve been working hard to bring this project to fruition, and today we’re excited to announce the Firefly Alpha Program (our code name for Aerospike’s graph database offering). Firefly combines Aerospike Database - the most scalable realtime NoSQL database with Apache TinkerPop™ - the most widely adopted graph computing framework. Through the alpha program, we will provide early access to Firefly prototypes, provide a channel for you to interact with the team and help shape the product roadmap. We want to hear your feedback, learn about your use cases and challenges with graph databases and together, build the most scalable realtime graph database on the planet. Be a part of the journey. Let's fearlessly scale graph technology together. If you’d like to sign up reach out to us at email@example.com. Limited spots available.