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Cache Grab: How Much Are You Leaving on the Table?

CSS Wizardry

For the longest time now, I have been obsessed with caching. I think every developer of any discipline would agree that caching is important, but I do tend to find that, particularly with web developers, gaps in knowledge leave a lot of opportunities for optimisation on the table. Want to know everything (and more) about HTTP cache?

Cache 247
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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. Redis Server: 5.07, x86/64. MongoDB server: 4.4.2, BangDB server: 2.0.0, Application example: user profile cache, where profiles are constructed elsewhere (e.g., Author & founder of BangDB. About YCSB.

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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

Cassandra serves as the backbone for a diverse array of use cases within Netflix, ranging from user sign-ups and storing viewing histories to supporting real-time analytics and live streaming. Developers just provide their data problem rather than a database solution!

Latency 260
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MySQL Data Caching Efficiency

Percona

A shared characteristic in most (if not all) databases, be them traditional relational databases like Oracle, MySQL, and PostgreSQL or some kind of NoSQL-style database like MongoDB, is the use of a caching mechanism to keep (a copy of) part of the data in memory. How do you know if your MySQL database caching is operating efficiently?

Cache 107
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Optimising for High Latency Environments

CSS Wizardry

Reduce Transfer Size Broadly simplified… Web servers don’t send whole files at once—they chunk them into packets and send those. permitted the opening of multiple simultaneous connections to a server at once. Interestingly, 304 responses are still a form of redirect: the server is redirecting your visitor back to their HTTP cache.

Latency 244
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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. million AI server units annually by 2027, consuming 75.4+

Cache 276
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Designing Instagram

High Scalability

When the server receives a request for an action (post, like etc.) We can use cloud technologies such as Amazon Kinesis or Azure Stream Analytics for collecting, processing, and analyzing real-time, streaming data to get timely insights and react quickly to new information(e.g. High Level Design. Architecture. Streaming Data Model.

Design 334