For cloud data engines, the separation of storage and compute has provided substantial benefits in terms of data durability, manageability, elasticity, and unit cost advantages versus previous on-premises analytical processing approaches.
However, the popular cloud data warehouses which leverage this, such as Snowflake and Google BigQuery, suffer from large and unpredictable latencies due to their storage design making them unsuitable for online transactional processing or interactive ad hoc queries serving users. Their sweet spot is the batch-heavy, “rearview mirror” analytical workloads.
Hear more from Joyo Victor, Software Engineer at SingleStore on our unique innovations in the area of separation of storage and compute with the incorporation of what we call “transactional durability” into SingleStore’s existing tiered storage model.
Learn more about how we support low-latency, high-throughput writes for transactional processing while still delivering all the benefits of the separation of storage and compute, usually seen with analytics-only systems. This unique combination extends the capabilities of SingleStore as the unified database for fast analytics and the ideal solution for data-intensive applications.
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Speakers:
The cloud-native operational database built for speed and scale
Accelerate business with instant insights delivered by the world’s fastest database for operational analytics
Create your future on a platform made for the demands of the data revolution, including machine learning and AI
Transform on your terms - with the familiarity and efficiency of SQL, and an architecture that bursts through limits