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Apache Flink VS skim (fuzzy finder)

Compare Apache Flink VS skim (fuzzy finder) and see what are their differences

Apache Flink logo Apache Flink

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

skim (fuzzy finder) logo skim (fuzzy finder)

Discover open source libraries, modules and frameworks you can use in your code
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • skim (fuzzy finder) Landing page
    Landing page //
    2023-09-13

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

skim (fuzzy finder) videos

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Category Popularity

0-100% (relative to Apache Flink and skim (fuzzy finder))
Big Data
100 100%
0% 0
Note Taking
0 0%
100% 100
Stream Processing
100 100%
0% 0
Productivity
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Flink seems to be a lot more popular than skim (fuzzy finder). While we know about 30 links to Apache Flink, we've tracked only 1 mention of skim (fuzzy finder). 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.

Apache Flink mentions (30)

  • Show HN: Restate, low-latency durable workflows for JavaScript/Java, in Rust
    Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 19 days ago
  • Array Expansion in Flink SQL
    I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / about 1 month ago
  • Show HN: An SQS Alternative on Postgres
    You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 2 months ago
  • 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 / 3 months 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 / 5 months ago
View more

skim (fuzzy finder) mentions (1)

  • Every NPM package potentially compromised
    That's great, thank you! Does it check recursive dependencies, and could you make it work against a package you haven't installed yet, by specifying the package name as an argument, rather than it only looking at what's already installed? If that's possible, it would be really good to then run it against a list of popular packages, like [1] or [2], and report back which packages are the highest priority for... - Source: Hacker News / over 2 years ago

What are some alternatives?

When comparing Apache Flink and skim (fuzzy finder), you can also consider the following products

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

fzf - A command-line fuzzy finder written in Go

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

fzy - A better fuzzy finder

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

Peco - Peco Foods, a poultry products provider for industrial, retail and food service markets, is dedicated to customer satisfaction, value and total quality management.