Case Study: How Armis cut data pipeline cost 70% with SingleStore
Key results
The challenge
Armis originally launched on PostgreSQL, then migrated its time-based dataset from 400+ databases into a 160-node Elasticsearch cluster ingesting 100 billion events per day. That pipeline required extensive supporting infrastructure and frequent full reindexes, costing more than $1 million annually while delivering poor query performance.
The solution
Armis consolidated onto SingleStore, running SingleStore Helios on AWS alongside SingleStore Self-Managed for FedRAMP environments, to unify high-volume ingestion and querying in a single platform.
“We moved from the entire data pipeline including ElasticSearch costing more than $1 million annually to paying a fraction of that for SingleStore Helios, reducing our data pipeline cost by 70%.”
ACAviram CohenChief R&D Officer, Armis
The results, in context
Armis reports a 70% reduction in data pipeline cost after replacing its Elasticsearch pipeline with SingleStore Helios, moving from more than $1 million annually to a fraction of that. The platform ingests 100 billion events and 1.2 billion sessions per day and loads roughly 1 million rows per second, with queries that previously timed out in Elasticsearch now completing in under 10 seconds.