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A time series database is a software system that is optimized for storing and serving time series through associated pairs of time(s) and value(s). [1] In some fields, time series may be called profiles, curves, traces or trends. [ 2 ]
Amazon DynamoDB is a managed NoSQL database service provided by Amazon Web Services (AWS). It supports key-value and document data structures and is designed to handle a wide range of applications requiring scalability and performance. [2]
Product (database) Amazon Timestream, a time series database [214] 2020 December 1 Product Amazon CodeGuru, a developer tool that uses machine learning-based recommendations to improve code quality [215] 2021 March 1 Regional diversification AWS expands Osaka Local Region (ap-northeast-3) to a standard AWS region with 3 Availability Zones [216 ...
As a document database, Amazon DocumentDB can store, query, and index JSON data. It is available on Amazon Web Services . [ 2 ] [ 3 ] As of March 2023, AWS introduced some compliance with MongoDB 5.0 but lacks time series collection support.
Functions like a RDBMS (structured data) for fast analytics on datasets in the hundreds of GBs to tens of TBs range. Interact with SQL and REST API. Geospatial objects and functions. UDF framework allows for custom code and machine learning workloads to run in-database. Received $50mil Series A funding in June 2017. [5] Memcached: Danga ...
Amazon Kinesis is a family of services provided by Amazon Web Services (AWS) for processing and analyzing real-time streaming data at a large scale. Launched in November 2013, it offers developers the ability to build applications that can consume and process data from multiple sources simultaneously. [2]
A time series database is a software system that is optimized for the handling of data organized by time. Time series are finite or infinite sequences of data items, where each item has an associated timestamp and the sequence of timestamps is non-decreasing. Elements of a time series are often called ticks.
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. Generally, time series data is modelled as a stochastic process.