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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. We will use a graph database such as Neo4j to store the information. Component Design. API Design. We have provided the API design of posting an image on Instagram below.

Design 334
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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. This article is to simply report the YCSB bench test results in detail for five NoSQL databases namely Redis, MongoDB, Couchbase, Yugabyte and BangDB and compare the result side by side. Again Yugabyte latency is quite high.

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Scalable Annotation Service?—?Marken

The Netflix TechBlog

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. All data should be also available for offline analytics in Hive/Iceberg. A data model in Marken can be described using schema — just like how we create schemas for database tables etc.

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Artificial Intelligence in Cloud Computing

Scalegrid

The partnership between AI and cloud computing brings about transformative trends like enhanced security through intelligent threat detection, real-time analytics, personalization, and the implementation of edge computing for quicker on-site decision-making. These services are tailored to meet various business requirements.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources.

Cache 209
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Redis vs Memcached in 2024

Scalegrid

Redis Data Types and Structures The design of Redis’s data structures emphasizes versatility. It is designed to cache plain text values, offering fast read and write access to frequently accessed data. Advanced Redis Features Showdown Big data center concept, cloud database, server power station of the future.

Cache 130
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Introducing Dynatrace built-in data observability on Davis AI and Grail

Dynatrace

Data observability is crucial to analytics and automation, as business decisions and actions depend on data quality. This freshness measurement can then be used by out-of-the-box Dynatrace anomaly detection to actively alert on abnormal changes within the data ingest latency to ensure the expected freshness of all the data records.

DevOps 197