All workloads with time series and all performance
There are several enhancements and updates being made available to the global user base. Although InfluxDB has always excelled at processing metrics, the new engine can not only process them, but also handle events and track with dramatic improvements in performance and efficiency.

There are currently no other time series data stores available that are optimized to index, store and analyze metrics, event and tracking data together in one place.

InfluxDB Cloud, with its new high-performance time series engine, can ingest, store and analyze high-volume, high-speed data in real-time and extract metrics on the fly from events at high granularity. This expands the number and variety of use cases that InfluxDB can handle, such as observability and distributed tracking that rely on high-cardinality data.

Lower cost of ownership
InfluxDB Cloud now uses Apache Parquet as its persistence format. This not only contributes to dramatic improvements in compression, but also allows users to extend the value of their time series data by passing it to other systems and ecosystems that use Parquet.

Optimized for low latency queries
Ingesting and storing data in InfluxDB is only half the story. The ability to efficiently search and use all that data is just as important. We’ve optimized the new engine for performance thanks to several under-the-hood updates. While concepts like parallelism, pushdown, and in-memory caching are critical aspects determining the performance of low-latency queries, what really matters to users is that fast and reliable queries improve the user experience.

The new database engine is available in two AWS regions (Virginia (us-east-1) and Frankfurt (eu-central-1)), but new availability zones are planned as well as adding availability for Azure and Google Cloud.