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Go to:Materialized views are a feature available with many databases to store the results of a frequently executed query so that the same view can be accessed repeatedly without forcing the database to re-execute the query each time. This allows for faster access to the data, as the results of the query do not need to…
High cardinality data can be more difficult to efficiently analyze because many unique elements increase the computational cost for analysis, and make it more challenging to identify useful insights from the data. Cardinality refers to the number of unique elements in a set. For instance, low cardinality data sets include the names of a few…
Streaming databases are close cousins to time-series databases (think TimescaleDB) or log databases (think Splunk). All are designed to track a series of events and enable queries that can search and produce statistical profiles of blocks of time in near real-time. Streaming databases can ingest data streams and enable querying of the data across larger…
As sensor data, log data and streaming data continues to grow, we are seeing a significant increase in demand for tools that can do spatial and time-series analytics. The cost of sensors and devices capable of broadcasting their longitude and latitude as they move through time and space is falling rapidly with commensurate proliferation. By…
A data firehose, or a data stream, is a continuous, high-volume flow of data that is produced by a data source. Common data firehoses include social media feeds, financial market data, and transponder data. High volume data streams are found in a variety of use-cases, including real-time analytics, fraud detection, and event-driven architectures. Data firehoses…
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