Inside Adobe’s real-time customer data platform: 89% savings leveraging Aerospike’s tiered storage engines
Adobe scaled its real-time customer data platform while cutting infrastructure costs by 89% using a two-tier Aerospike architecture with SSD and RAM.
How do you deliver real-time, personalized experiences across millions of users, under tight latency service level agreements (SLAs), at a global scale, while keeping costs under control?
That’s the challenge Adobe faces every day. Its real-time customer data platform (CDP) processes billions of profiles, handles tens of billions of writes per day, and serves millions of reads daily across a global edge network. It processes massive streams of behavioral data, creates unified customer profiles, and activates them for personalization in milliseconds. Every millisecond matters, and every dollar counts.
To meet those demands, Adobe engineers designed a new kind of data layer—one powered by a tiered storage Aerospike architecture. The result?
✅ Faster performance
✅ Fivefold increase in scale
✅ Reduced infrastructure costs by 89%
This post is based on a talk by Anuj Jain, Senior Engineering Manager at Adobe, delivered at the Real-Time Data Summit.

What personalization at the edge demands
Adobe’s personalization engine powers dynamic web content, in-app product recommendations, and real-time audience segmentation. These aren’t batch jobs—they happen live, in milliseconds, with users expecting immediate, tailored experiences.

Adobe’s real-time CDP ingests behavioral data from known and anonymous users across every touchpoint, creates identities on the fly, and activates segments for marketing, analytics, and experience delivery.
One example is on-site and in-app personalization, triggered by client software development kits (SDKs) through Adobe’s Edge Network. “From there, they are sent to the different services on the Adobe Edge, to read the profiles, perform segmentation, and carry out other personalization activities, ultimately delivering a personalized experience to the visitor on the web page,” Jain said. “Additionally, all these incoming events are also collected in the Adobe real-time CDP for further processing, detailed analysis, and analytics.”
The cost of memory at scale
To meet Adobe’s real-time SLA targets, performance wasn’t optional—it was foundational. Every request had to fetch and process a user profile, run segmentation, and complete a round-trip to the edge.