Software Alternatives & Reviews

Apache Flink VS Snowflake

Compare Apache Flink VS Snowflake 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.

Snowflake logo Snowflake

Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • Snowflake Landing page
    Landing page //
    2022-12-29

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

Snowflake videos

Grand Seiko Spring Drive "Snowflake" SBGA211 Luxury Watch Review

More videos:

  • Review - BEST GRAND SEIKO? Snowflake SBGA211 Review
  • Review - Grand Seiko Snowflake SBGA211 - Review and Impressions

Category Popularity

0-100% (relative to Apache Flink and Snowflake)
Big Data
61 61%
39% 39
Stream Processing
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Databases
73 73%
27% 27

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Flink and Snowflake

Apache Flink Reviews

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Snowflake Reviews

Top 6 Cloud Data Warehouses in 2023
Snowflake accommodates data analysts of all levels since it does not use Python or R programming language. It is also well known for its secure and compressed storage for semi-structured data. Besides this, it allows you to spin multiple virtual warehouses based on your needs while parallelizing and isolating individual queries boosting their performance. You can interact...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Snowflake is one of the most popular data warehousing solutions on the market and delivers an incredible experience across multiple public clouds. By using Snowflake, companies can pull data from various business intelligence tools to do reporting and analytics without any database administration, thus avoiding high overhead costs. Unlike other data warehousing services,...
Top 5 BigQuery Alternatives: A Challenge of Complexity
Plus, Snowflake doesn’t include data integrations, so teams will have to bolt on an ETL tool to pipe their data into the warehouse. Those third-party pipelines add extra cost and overhead in the form of setup and maintenance that some teams may not want to absorb.
Source: blog.panoply.io
Top Big Data Tools For 2021
This platform can be used for data warehousing, data science, data engineering, sharing, and application development. It enables you to easily secure your data and execute various analytic workloads. Snowflake also ensures a seamless experience when working with multiple public clouds.

Social recommendations and mentions

Based on our record, Apache Flink should be more popular than Snowflake. It has been mentiond 27 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.

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 / 14 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 / 2 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 / 4 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 / 4 months ago
View more

Snowflake mentions (4)

  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Snowflake, a data warehousing company founded by ex-Oracle and ex-VectorWise experts, responded with a blog post that critically reviewed Databricks' findings, reported different results for the same benchmark, and claimed comparable price/performance to Databricks. - Source: dev.to / almost 2 years ago
  • Personal Support at Internet Scale
    Snowflake: Snowflake is fast, and works well as a product analytics database. - Source: dev.to / over 2 years ago
  • Less than 1TB of data what tools should I get better at?
    If you just go to snowflake.com you can sign up for a demo account for free for a month and I'm fairly certain you can get more than one of these accounts (I would recycle emails doing it all the time.) Once you have an account there's lots of docs and videos out there either using the Database via their UI or via python using their connector. They also have a pyspark connector but you might want to just learn... Source: over 2 years ago
  • *BOMATO*
    Early stage funding & VCs clearly demarcate between tech companies and tech enabled companies. But, once the PE comes into the picture at the scale of BlackStone, the border between doordash.com and snowflake.com starts to blur. The motivation is to make some bucks by going to IPO and they know how to get it done. Source: over 2 years ago

What are some alternatives?

When comparing Apache Flink and Snowflake, 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.

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

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

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

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

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