SingleStore’s unified database can set analytics and dashboards free from chronic sluggish performance. This blog is a recap of a webinar on Data Warehouse Augmentation, presented by Rick Negrin and Vijay Raja of SingleStore’s product management team. This blog captures the highlights of this webinar and includes details on three patterns that SingleStore can augment in today’s data warehouses to enable low latency, sub-millisecond performance at-scale.
Is your Data Warehouse delivering the goods?
Whether on premises or in the cloud, data warehouses have been around for decades. They’re the back-end workhorses in myriad use cases involving analytics, reporting and business intelligence (BI), querying massive amounts of aggregated data sets. But even though today’s most popular data warehouses (such as Snowflake, Amazon Redshift, Google BigQuery, Vertica and Teradata) have been born in the cloud or re-architected for it, they are increasingly challenged to meet user expectations and service level agreements (SLAs) for the real-time data ingest and millisecond query responses that are needed to power today’s data-intensive applications.
SingleStore recently put together an information-packed webinar, “20x Faster Analytics through Data Warehouse Augmentation,” that dove into the details of how our unified database can set analytics and dashboards free from chronic sluggish performance. This blog is a recap of the webinar, presented by Rick Negrin and Vijay Raja of SingleStore’s product management team, and includes details on three patterns that SingleStore can augment in today’s data warehouses to enable low latency, sub-millisecond performance at-scale.
Four types of performance bottlenecks
Let’s jump into the webinar at about the eight-minute mark, as Vijay details the types of key challenges or bottlenecks that data warehouse workflows typically face.
Key capabilities for fast analytics
To address these shortcomings, customers across diverse verticals are augmenting their data warehouses with SingleStore, powering some of their most data-intensive applications to support fast analytics. SingleStore brings three key capabilities that enable fast analytics through data warehouse augmentation:
Three ways to augment data warehouses:
Rick then took over the mic to explain ‘the how’ SingleStore augments data warehouse, describing three prominent patterns and their efficacy in specific use cases.
Here, time-sensitive data or real-time data can be directly streamed into SingleStore using SingleStore Pipelines, while the rest of the data is loaded into the data warehouse via a batch-ingestion process. When queried, a serving layer merges both views to generate appropriate results.
The raw data is dropped in an event queue such as Kafka, perhaps in a single star schema with some light transformation. Aggregation is done on the fly, as part of the query to power the dashboards. SingleStore’s streaming data ingestion capabilities are a critical enabler of fast dashboard performance.
Powerful use cases
The last part of the webinar was filled with detailed customer examples and Q&A with the audience. Rick walked through several impressive customer examples:
Yes, there’s more, a lot more! To hear all the technical details about the customer studies, and get a more detailed view into how SingleStore can improve the performance of data warehouse-derived analytics, watch the on-demand webinar now.
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