​Previous workshop:

​Scale your graph workloads with multi-tenancy

​⏰ PDT: 10:00 AM | EDT: 1:00 PM | CEST: 7:00 PM

​If you’re running a SaaS and each client gets their own graph, things get interesting fast. Start with ten clients, ten graphs—easy. What happens when you scale to ten thousand?.

​With other graph databases, performance degrades as each tenant adds load, and you're soon throwing hardware at the problem. 

​We see SaaS providers and enterprises struggling with this constantly. The usual answer is to scale vertically, or throw more CPU and RAM at the problem.

​This is expensive and has diminishing returns.

​That’s why we designed FalkorDB from the ground up to handle multi-tenancy efficiently. The key is how we’ve combined a high-performance core with clustering and resource management.

​This workshop is designed for data scientists, aI/ML architects, and software developers familiar with graph databases. It addresses the challenges of scaling graph workloads in multi-tenant environments, offering practical solutions to common pain points such as performance degradation, increased infrastructure costs, and management complexity.

​Why attend:

​📍 Learn how multi-tenancy lets you scale your graph workloads efficiently and cost-effectively, which is relevant if you're running a SaaS with multiple clients and graphs (or planning to!)

​📍 See how FalkorDB's architecture handles high throughput and low latency, supporting up to 1 million transactions per second

​📍 Understand how FalkorDB achieves superior performance with considerably fewer compute resources compared to alternatives like Neo4j and Memgraph

​📍 See how to implement multi-tenancy in FalkorDB, covering cluster support, tenant isolation, resource allocation, and security considerations