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.NET for Apache Spark VS Redis ™

Compare .NET for Apache Spark VS Redis and see what are their differences

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.NET for Apache Spark logo .NET for Apache Spark

.NET for Apache Spark™ provides C# and F# language bindings for the Apache Spark distributed data analytics engine. Supported on Linux, macOS, and Windows.

Redis logo Redis

Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
  • .NET for Apache Spark Landing page
    Landing page //
    2023-05-23
  • Redis Landing page
    Landing page //
    2022-10-19

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.

.NET for Apache Spark videos

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Redis videos

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Improve your Redis developer experience with RedisInsight, Redis Labs

More videos:

  • Review - What is Redis? | Why and When to use Redis? | Tech Primers
  • Review - Redis Enterprise Overview with Yiftach Shoolman - Redis Labs
  • Review - Redis Labs "Why NoSQL is a Safe Bet"
  • Review - Redis system design | Distributed cache System design
  • Review - What is Redis and What Does It Do?
  • Review - Redis Sorted Sets Explained

Category Popularity

0-100% (relative to .NET for Apache Spark and Redis)

.NET for Apache Spark

Redis

PHP Web Framework
100 100%
PHP Web Framework
0% 0
Databases
0 0%
Databases
100% 100
Data Integration
100 100%
Data Integration
0% 0
NoSQL Databases
0 0%
NoSQL Databases
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare .NET for Apache Spark and Redis

.NET for Apache Spark Reviews

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Redis Reviews

Are Free, Open-Source Message Queues Right For You?
A notable challenge with Redis Streams is that it doesn't natively support distributed, horizontal scaling. Also, while Redis is famous for its speed and simplicity, managing and scaling a Redis installation may be complex for some users, particularly for persistent data workloads.
Source: blog.iron.io
Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
1. Redis: I'll start with Redis which I'd like to call the "original" key/value store (after memcached) because it is the oldest and most widely used of all. Being a long-time follower of Redis, I do know it's single-threaded (and uses io-threads since 6.0) and hence it achieves lesser throughput than the other stores listed above which are multi-threaded, at least to some...
Source: news.ycombinator.com
Memcached vs Redis - More Different Than You Would Expect
Remember when I wrote about how Redis was using malloc to assign memory? I lied. While Redis did use malloc at some point, these days Redis actually uses jemalloc. The reason for this is that jemalloc, while having lower peak performance has lower memory fragmentation helping to solve the framented memory issues that Redis experiences.
Source: engineering.kablamo.com.au
Top 15 Kafka Alternatives Popular In 2021
Redis is a known, open-source, in-memory data structure store that offers different data structures like lists, strings, hashes, sets, bitmaps, streams, geospatial indexes, etc. It is best utilized as a cache, memory broker, and cache. It has optional durability and inbuilt replication potential. It offers a great deal of availability through Redis Sentinel and Redis Cluster.
Source: www.spec-india.com
Comparing the new Redis6 multithreaded I/O to Elasticache & KeyDB
So there are 3 offerings by 3 companies, all compatible with eachother and based off open source Redis: Elasticache is offered as an optimized service offering of Redis; RedisLabs and Redis providing a core product and monetized offering, and KeyDB which remains a fast cutting edge (open source) superset of Redis. This blog looks specifically at performance, however there is...
Source: docs.keydb.dev

Social recommendations and mentions

Based on our record, Redis seems to be a lot more popular than .NET for Apache Spark. While we know about 187 links to Redis, we've tracked only 3 mentions of .NET for Apache Spark. 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.

.NET for Apache Spark mentions (3)

  • Debug dotnet Spark using Databricks-connect
    I assume you are talking about this https://dotnet.microsoft.com/en-us/apps/data/spark. Source: almost 2 years ago
  • Microsoft Announces new Scalable Machine Learning Library for .NET
    Good question! The API and the authoring experience is .NET, but the backend is Apache Spark which is built on the JVM. We use the .NET for Apache Spark to do the parallization. Source: almost 2 years ago
  • Microsoft Announces new Scalable Machine Learning Library for .NET
    Yes that's correct. SynapseML builds on top of the Apache Spark for .NET project which provides .NET support for the Apache Spark distributed computing framework. Apache Spark is written in Scala (a language on the JVM) but has language bindings in Python, R, .NET and other languages. This release adds full .NET language support for all of the models and learners in the SynapseML library so you can author... Source: almost 2 years ago

Redis mentions (187)

  • Shades of Open Source - Understanding The Many Meanings of "Open"
    Many popular open source projects are beloved and closely tied to particular vendors. For example, web frameworks like React and Angular are associated with Meta and Google, respectively. Database software like MongoDB, Elasticsearch, and Redis are also tied to specific commercial entities but are widely used and praised for their functionality. When there is a clear driver of a project, it can offer some benefits:. - Source: dev.to / about 23 hours ago
  • How to Setup a Project That Can Host Up to 1000 Users for Free
    One of the most effective ways to improve the application’s performance is caching regularly accessed data. There are two leading key-value stores: Memcached and Redis. I prefer using Memcached Cloud add-on for caching because it was originally intended for it and is easier to set up, and using Redis only for background jobs. - Source: dev.to / 11 days ago
  • Hanami and HTMX - progress bar
    Hi there! I want to show off a little feature I made using hanami, htmx and a little bit of redis + sidekiq. - Source: dev.to / about 1 month ago
  • What do you want to watch next? This is why I built GoodWatch.
    Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance. - Source: dev.to / about 1 month ago
  • Redis is not "open core" (2021)
    The page 404s for me currently and it does not seem to be archived by the wayback machine either: https://web.archive.org/web/20240000000000*/https://redis.io/news/121. - Source: Hacker News / 2 months ago
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What are some alternatives?

When comparing .NET for Apache Spark and Redis, you can also consider the following products

Apache Flume - Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Vertica - Vertica is a grid-based, column-oriented database designed to manage large, fast-growing volumes of...

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

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