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Redis ™ VS Google Cloud Dataproc

Compare Redis VS Google Cloud Dataproc and see what are their differences

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Redis logo Redis

Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • 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.

  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Redis videos

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What is Redis? | Why and When to use Redis? | Tech Primers

More videos:

  • Review - Improve your Redis developer experience with RedisInsight, Redis Labs
  • Review - Redis Labs "Why NoSQL is a Safe Bet"
  • Review - Redis Enterprise Overview with Yiftach Shoolman - Redis Labs
  • Review - Redis system design | Distributed cache System design
  • Review - What is Redis and What Does It Do?
  • Review - Redis Sorted Sets Explained

Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to Redis and Google Cloud Dataproc)

Redis

Google Cloud Dataproc

Databases
100 100%
Databases
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Big Data
0 0%
Big Data
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 Redis and Google Cloud Dataproc

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

Google Cloud Dataproc Reviews

We have no reviews of Google Cloud Dataproc yet.
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Social recommendations and mentions

Based on our record, Redis seems to be a lot more popular than Google Cloud Dataproc. While we know about 185 links to Redis, we've tracked only 3 mentions of Google Cloud Dataproc. 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.

Redis mentions (185)

  • 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 / 6 days 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 / 7 days 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 / about 1 month ago
  • Software Engineering Workflow
    Redis - real time data storage with different data structures in a cache. - Source: dev.to / about 1 month ago
  • Redis License Changed
    Redis.io no longer mentions open source. They have still not changed meta description on their page. It still says it is open source ^^ view-source:https://redis.io/. - Source: Hacker News / about 2 months ago
View more

Google Cloud Dataproc mentions (3)

  • Connecting IPython notebook to spark master running in different machines
    I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
  • Why we don’t use Spark
    Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
  • Data processing issue
    With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago

What are some alternatives?

When comparing Redis and Google Cloud Dataproc, you can also consider the following products

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

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

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

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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