Real-Time Data Warehousing for the Real-Time Economy

In the traditional data warehouse era, enterprises relied on batch processes to generate analyses and reports, utilizing extraction, transformation, and load (ETL) processes to standardize disparate data into normalized schemas. In contrast, today's real-time economy demands perpetual data ingest, simultaneous reads, high user concurrency, and fast queries, making it necessary for businesses to shift towards real-time data storage and analytics. Companies like Pinterest, Uber, and Pandora have achieved significant performance advantages by adopting this approach, as stated by Eric Frenkiel, SingleStore co-founder and CEO. The real-time data warehouse is designed to continually load and transform data, enabling applications to run on top of it with exactly-once semantics. With a hybrid cloud data warehouse like SingleStore, businesses can push real-time workloads where they are most economical to run, offering cost-savings advantages in the process.

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