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Google Cloud Dataflow VS Redis ™

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

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Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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 Dataflow Landing page
    Landing page //
    2023-10-03
  • 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 Dataflow videos

+ Add

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Redis videos

+ Add

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

Category Popularity

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

Google Cloud Dataflow

Redis

Big Data
100 100%
Big Data
0% 0
Databases
0 0%
Databases
100% 100
Data Dashboard
100 100%
Data Dashboard
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 Google Cloud Dataflow and Redis

Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

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 Google Cloud Dataflow. While we know about 185 links to Redis, we've tracked only 14 mentions of Google Cloud Dataflow. 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.

Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago
  • Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago
  • Why we don’t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 2 years ago
View more

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 / 4 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 / 6 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

What are some alternatives?

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

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

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.

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

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

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