Centralize caching for uniformly performant data
Cube's semantic layer enables cost-effective work with billion-row datasets and subsecond responses while orchestrating caching upstream of all of your data apps — once.
and 50+Leverage an in-memory cache and queue that ward off latency
Cube's two-level caching system uses an in-memory cache, queue management, and configurable pre-aggregations. Cube's in-memory cache and queue management capabilities are based on our proprietary Cube Store; together, they serve as a buffer for your database when there's an influx of concurrent requests hitting your database, allowing you to scale stateless API instances horizontally and making APIs idempotent.
Maximize data performance to make sure it matches your speed
Cube's caching layer comes with configurable pre-aggregations, a layer of aggregated data built and refreshed by attributes and intervals you set. Access the condensed, cached version of your data to maximize speed and minimize latency.
Save your capital for more important things than redundant queries
Why spend unnecessary capital (and time) to query operationalized data directly from data sources? Redundant queries result in latency and major cost-inefficiency. Streamline your pipeline by querying Cube's cache — and watch your bills drop.
Orchestrate your caching layer once — and only once
Since Cube is a middleware that sits between your data source and applications, it's upstream of every data app your organization uses. Therefore, its position in the data pipeline means that you don't need to manually orchestrate caching for every application, saving you effort and ensuring that your applications are uniformly performant and coordinated. And, Cube's Orchestration API makes connecting your orchestration tools a matter of minutes.
“We found an incredibly fast-to-market and flexible modern analytics solution: Cube. We were able to deliver a complex but highly customized embedded analytics user experience—in two weeks, and without changing our stack.”
