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What Is Streaming Analytics?

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Feed: SingleStore Blog.
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Optimized architecture: Columnstore databases traditionally have been restricted to data warehouse uses where low latency queries are a secondary goal. Data ingestion is typically restricted to be offline, batched, append-only or some combination thereof.

To handle streaming analytics, a column store database implementation must treat low latency queries and ongoing writes as “first-class citizens,” with a focus on avoiding interference between read, ingest, update and storage optimization workloads. This broadens the range of viable column store workloads to include streaming analytics, and their stringent demands on query and data latency. These applications include operational systems that back adtech, financial services, fraud detection and other data streaming applications.

SingleStoreDB is a modern, unified, real-time distributed SQL database. It uses fragmented snapshot transactions and optimistic storage reordering to meet the extremely low latency requirements of streaming analytics applications. SingleStoreDB stores data in tables and supports standard SQL data types. Geospatial and JSON data types are also first-class citizens in SingleStoreDB, which can store and query structured, semi-structured and unstructured data with equal ease.

In SingleStoreDB, a table is either distributed or non-distributed (e.g., a reference table). There are two storage types for tables: in-memory rowstore and columnstore. All columnstore tables have an unexposed, in-memory rowstore table. SingleStoreDB automatically spills rows from the in-memory rowstore to columnstore. All data, including the hidden rowstore table, is queryable for the columnstore table.

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