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This article was published as a part of the Data Science Blogathon. Introduction DuckDB is designed to support analytical query workloads, also known as Onlineanalyticalprocessing (OLAP).” In short, […].
This article was published as a part of the Data Science Blogathon. Introduction In the field of Data Science main types of onlineprocessing systems are Online Transaction Processing (OLTP) and OnlineAnalyticalProcessing (OLAP), which are used in most companies for transaction-oriented applications and analytical work.
Data outbound Data is often consumed using structured queries for analytical needs. Also, datasets are accessed for ML, data exporting, and publishing needs. This service is the core of this reference architecture on AWS and can address most analytical needs out of the box.
A loading team builds a producer-consumer architecture in Amazon Redshift to process concurrent near real-time publishing of data. This requires a dedicated team of 3–7 members building and publishing refined datasets in Amazon Redshift. The data warehouse is highly business critical with minimal allowable downtime.
Amberdata, a blockchain and crypto market intelligence company, uses StarTree for real-time analytics to improve query performance, reduce SLA times, and lower infrastructure costs. Like Pinot, StarTree addresses the need for a low-latency, high-concurrency, real-time onlineanalyticalprocessing (OLAP) solution.
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