Discover why and how GE Healthcare employed Scylla's DynamoDB-compatible API (Alternator) to provide precision medical diagnoses in their Edison AI solution.
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Learn about the challenges of building an ML system with the low latency required to support the high volume and high throughput demands of ad serving.
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Delve into the fundamentals of ML feature stores and explore why and how ScyllaDB can be a critical part of your feature store architecture.
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TRACTIAN's comparison of ScyllaDB vs MongoDB and PostgreSQL, plus their migration challenges & results.
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Introduces MLOps at Instacart, outlines Griffin system design, and shares our learnings in building Griffin to empower product innovations at Instacart.
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Sandeep Lakshmipathy, Director of Engineering for Edison AI, discusses how Scylla helped GE Healthcare respond to health providers’ requirements by extending to a hybrid model with some data in Amazon
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Alex Bantis describes how ScyllaDB helped Tubi to unify ML-driven apps with Scala and Spark.
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ScyllaDB enables rapid Machine Learning experimentation at Tubi. The current-generation personalization service, Ranking Service, ramps up experimentation by 5x, while Popper, the next-generation expe
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SmartDeployAI builds data workflow pipelines for running large scale Industrial IoT applications. Their software platform is a shared multi-tenant Kubernetes cluster environment where multiple workflo
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“I’ve worked with BigTable, Redis, Postgres and DynamoDB. Compared to all of these Scylla provides very low latencies and has been inexpensive and easy to deploy.” – Rohit Saboo, ML Infrastructure Lea
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Daniel Barsky discusses the reasons behind Augury's choose of Scylla over Cassandra.
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Augury stores and serves time-series features from massive streams of IoT data. Learn about their needs and constraints, their data architecture, and their data modeling approach.
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How Amdocs optimizes complex data and AI pipelines for the modern telecom, including diagnostics and predictive analytics.
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KairosDB is an open-source time-series database that uses Scylla or Cassandra as a back-end datastore. Time-series databases are vital for a wide variety of use cases, from vehicle tracking to industr
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