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Scalable Annotation Service?—?Marken

The Netflix TechBlog

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency.

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Designing Instagram

High Scalability

Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design. Component Design. API Design. We have provided the API design of posting an image on Instagram below. API Design. Problem Statement. Architecture. Fetching User Feed.

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Artificial Intelligence in Cloud Computing

Scalegrid

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Predictive analytics, powered by AI, enhance business processes and optimize resource allocation according to workload demands.

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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

This is guest post by Sachin Sinha who is passionate about data, analytics and machine learning at scale. We note that for MongoDB update latency is really very low (low is better) compared to other dbs, however the read latency is on the higher side. Again Yugabyte latency is quite high. Author & founder of BangDB.

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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Designed to help scalable applications deliver high performance, it stores live, fast-changing data in memory (DRAM) for fast updates and retrieval. It also transparently makes use of the IMDG’s scalable computing resources to accelerate the analysis.

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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Designed to help scalable applications deliver high performance, it stores live, fast-changing data in memory (DRAM) for fast updates and retrieval. It also transparently makes use of the IMDG’s scalable computing resources to accelerate the analysis.

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Data Reprocessing Pipeline in Asset Management Platform @Netflix

The Netflix TechBlog

Production Use Cases Real-Time APIs (backed by the Cassandra database) for asset metadata access don’t fit analytics use cases by data science or machine learning teams. This feature support required a significant update in the data table design (which includes new tables and updating existing table columns).

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