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.
Join us for a 45-minute Tech Talk, to learn more about:
- The benefits of separation of storage and compute
- How SingleStore durability and storage work under the hood, including SingleStore’s unique Integrated Durability and Compute capability
- The benefits of Integrated Durability and Compute over analytics only systems like Snowflake
- Joyo Victor, Software Engineer, SingleStore
- Eric Hanson, Product Management, SingleStore