Best Time Series Databases for Amazon S3

Find and compare the best Time Series Databases for Amazon S3 in 2025

Use the comparison tool below to compare the top Time Series Databases for Amazon S3 on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Cortex Reviews

    Cortex

    The Cortex Authors

    Cortex is an open-source project that adds horizontal scaling. Prometheus can scale upto 1 million samples/sec, but Cortex's horizontal scalability makes it practically inexhaustible. You need other methods to monitor individual servers or VMs in a dynamic environment. Prometheus' pull-based, service-discovery-driven metrics system was created for the dynamic nature microservices. It allows you to monitor your entire environment, regardless of how many moving parts. You can use the standard Prometheus client library to create custom metrics or you can take advantage of the many Prometheus exporters that collect data from applications such as MySQL, Redis Java, Java, ElasticSearch, and many others.
  • 2
    Warp 10 Reviews
    Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.
  • Previous
  • You're on page 1
  • Next