Case Study: Meta Networks achieves a scalable, low-latency streaming data lake on S3 with Upsolver

Meta Networks - Customer Case Study

Meta Networks, a fast-growing Network-as-a-Service (NaaS) provider, needed a scalable way to collect and manage massive, real-time streams of network logs for security research, monitoring and customer-facing analytics. As volume grew from dozens of GBs to hundreds of TBs per month, the team sought a self-service data lake on AWS S3 that non–big-data engineers could operate, with seamless connections to Athena and Elasticsearch — and they evaluated and chose Upsolver to meet those needs.

Using Upsolver to ingest Kinesis streams, transform and join data in-flight, and persist optimized datasets to S3 (with outputs to Athena and Elasticsearch), Meta Networks went from evaluation to production in under three weeks with a single developer. Upsolver enabled sub‑second to 1 second query latencies, terabytes of streaming data processed daily, continued single‑engineer operations, and saved tens of thousands of dollars in implementation and maintenance costs while delivering real-time, customer-facing analytics.

Meta Networks

Alon Horowitz

Co-founder and VP R&D