Software Alternatives & Reviews

Redis VS Apache Flink

Compare Redis VS Apache Flink and see what are their differences

Redis logo Redis

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

Apache Flink logo Apache Flink

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

  • Apache Flink Landing page
    Landing page //
    2023-10-03

Redis videos

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

Apache Flink videos

GOTO 2019 • Introduction to Stateful Stream Processing with Apache Flink • Robert Metzger

More videos:

  • Tutorial - Apache Flink Tutorial | Flink vs Spark | Real Time Analytics Using Flink | Apache Flink Training
  • Tutorial - How to build a modern stream processor: The science behind Apache Flink - Stefan Richter

Category Popularity

0-100% (relative to Redis and Apache Flink)
Databases
92 92%
8% 8
Big Data
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
Stream Processing
0 0%
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 Apache Flink

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...
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.
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.
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

Apache Flink Reviews

We have no reviews of Apache Flink yet.
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Social recommendations and mentions

Based on our record, Redis should be more popular than Apache Flink. It has been mentiond 183 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.

Redis mentions (183)

  • 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 / 24 days ago
  • Software Engineering Workflow
    Redis - real time data storage with different data structures in a cache. - Source: dev.to / 26 days 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 1 month ago
  • Tutorial: Install Redis in Distro Linux: Pop!_OS
    Follow the steps below to install Redis:. - Source: dev.to / about 2 months ago
  • How to choose the right type of database
    Redis: An open-source, in-memory data structure store supporting various data types. It offers persistence, replication, and clustering, making it ideal for more complex caching requirements and session storage. - Source: dev.to / 2 months ago
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Apache Flink mentions (27)

  • Top 10 Common Data Engineers and Scientists Pain Points in 2024
    Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 23 days ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
    Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 5 months ago
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What are some alternatives?

When comparing Redis and Apache Flink, you can also consider the following products

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

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

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

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

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

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.