Edge Computing


Storage capacity ​

Edge devices have limited storage capacity compared to servers, which limits the amount of data stored on the device​.

Processing power

Edge devices have limited processing power compared to cloud-based systems, which makes it challenging to analyze and large volumes of data in real-time​.

Performance impact

Data ingestion and storage can consume system resources and impact the performance of edge devices. This can lead to unresponsiveness and failures.​

Bandwidth ​

Edge devices are sometimes deployed in locations with limited bandwidth, which can make it challenging to transmit data to other systems for storage or analysis. ​


Limited ingestion speed

SQLite’s limited ingestion speed prevents it from being used in many applications with high data volume.

Constrained compression ratio​

The insufficient compression ratio of SQLite seriously limits the history capabilities of the device.

Inadequate streaming analytics ​

SQLite is slow on data aggregation, which further amplifies the ingestion and compression problems and increases CPU usage​.


1. Industry-leading data compression ratio of 40:1

Thanks to industry-proven, patented compression algorithms, Quasar Edge compresses data faster than it arrives, significantly reducing disk usage while enabling fast queries. This is especially important for edge computing with a limited storage capacity.

2. Ingestion: millions of rows per second on edge devices

Achieved through streaming compression,  novel data structures, and an innovative hybrid in-memory/disk architecture, Quasar Edge has a track record of handling large data sets even despite the constraints of an edge device.

3. No latency: real-time data analytics

In addition to data compression and fast ingestion capabilities, Quasar Edge also offers real-time, streaming data analytics,  and an extremely optimized query engine for time-series data, delivering powerful, immediate analytics, right at the edge.

4. Small footprint

Quasar Edge is a lightweight, self-contained database engine that is well-suited for edge devices due to its efficiency, small footprint, and low resource requirements. It supports a wide range of architectures from ARM32 to Intel x64.

5. Quick deployment

Quasar Edge supports SQL queries, a native Python interface, and all the standards your business depends on, which makes it easier for industrial engineers and analysts to access and analyze data without requiring specialized programming skills.

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