memcached
Redis
MongoDB
Aerospike
Apache Cassandra
ArangoDB
CouchDB
PostgreSQL
KubeMastery
KodeKloud
I wanted to learn Kubernetes, but the options were either "build a local lab" or pay for expensive classes built around cloud environments. I wanted something you could just open and learn from. So I built a browser-based cluster simulation with lessons to follow along.
It behaves like Kubernetes, but it's just JavaScript under the hood. Enough to run kubectl commands, create resources, and watch their lifecycle play out. There's also a live cluster visualizer so you can see your nodes, Pods, and containers in real time.
Once you've covered the concepts, you can jump into CKA drills. Each drill is a standalone, time-boxed scenario that mirrors the real exam format: a broken cluster state, a concrete task, and a pass-or-fail outcome.
The goal isn't to simulate the exam. It's to build the reflex of diagnosing and fixing things quickly, so that when you sit the real exam, the commands and the reasoning are already automatic.
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Based on our record, memcached seems to be more popular. It has been mentiond 37 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Memcached has a single, focused goal: to be a high-performance, distributed, in-memory object caching system. It stores all data in RAM, which means reads and writes are incredibly fast. But its main weakness is just as clear: data is completely lost when the service restarts, as it offers no persistence. Its data model is a simple key-value store, limited to basic get, set, and delete operations. - Source: dev.to / 12 months ago
Memcached can help when lightning-fast performance is needed. These tools store frequently accessed data, such as session details, API responses, or product prices, in RAM. This reduces the laid on your primary database, so you can deliver microsecond response times. - Source: dev.to / over 1 year ago
In-memory tools like Redis or Memcached for fast Data retrieval. - Source: dev.to / over 1 year ago
A caching layer using popular in-memory databases like Redis or Memcached can go a long way in addressing Postgres connection overload issues by being able to handle a much larger concurrent request load. Adding a cache lets you serve frequent reads from memory instead, taking pressure off Postgres. - Source: dev.to / over 1 year ago
Memcached โ Free and well-known for its simplicity, Memcached is a distributed and powerful memory object caching system. It uses key-value pairs to store small data chunks from database calls, API calls, and page rendering. It is available on Windows. Strings are the only supported data type. Its client-server architecture distributes the cache logic, with half of the logic implemented on the server and the other... - Source: dev.to / almost 2 years ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
KodeKloud - We are a fast growing EdTech startup on trending technologies in IT and Cloud Computing.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Aerospike - Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
