Source: thenewstack.io
Meet Scale and SLA Demands in Real-Time Data Architectures
Companies have gathered years of data into an incredible store of information, with new data streaming in at skyrocketing rates. It’s easy to build something that works well for a few people or a small amount of data.
Every company is racing to build applications and deliver real-time transactions and exceptional user experiences to millions of users as quickly as possible.
Let’s look at the various levers that are required for delivering high throughput at scale for demanding real-time applications, including massive parallelism, indexing and interoperability.
Beyond the data-processing side of your data architecture, you also need parallel architecture in query layers and streaming pipeline layers.
Every company is racing to build applications and deliver real-time transactions and exceptional user experiences to millions of users as quickly as possible.
Let’s look at the various levers that are required for delivering high throughput at scale for demanding real-time applications, including massive parallelism, indexing and interoperability.
Beyond the data-processing side of your data architecture, you also need parallel architecture in query layers and streaming pipeline layers.
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