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MySQL VS Apache Flink

Compare MySQL VS Apache Flink and see what are their differences

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MySQL logo MySQL

The world's most popular open source database

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
  • MySQL Landing page
    Landing page //
    2022-06-17
  • Apache Flink Landing page
    Landing page //
    2023-10-03

MySQL features and specs

  • Reliability
    MySQL is known for its reliability and durability, making it a solid choice for many businesses' database management needs.
  • Performance
    It offers robust performance, handling large databases and complex queries efficiently.
  • Open Source
    MySQL is an open-source database, making it freely available under the GNU General Public License (GPL).
  • Scalability
    MySQL supports large-scale applications and can handle high volumes of transactions.
  • Community Support
    There is a large, active MySQL community that offers extensive resources, documentation, and support.
  • Cross-Platform
    MySQL is compatible with various operating systems like Windows, Linux, and macOS.
  • Integrations
    MySQL integrates well with numerous development frameworks, including LAMP (Linux, Apache, MySQL, PHP/Python/Perl).
  • Security
    MySQL offers various security features, such as user account management, password policies, and encrypted connections.
  • Cost
    The open-source nature of MySQL means that it can be very cost-effective, especially for small to medium-sized businesses.

Possible disadvantages of MySQL

  • Support
    While community support is plentiful, official support from Oracle can be quite expensive.
  • Complexity
    More advanced features and configurations can be complex and may require a steep learning curve for new users.
  • Scalability Limitations
    While MySQL is scalable, very high-scale applications may run into limitations compared to some newer database technologies.
  • Plug-in Storage Engines
    The use of plug-in storage engines like InnoDB or MyISAM can cause inconsistencies and complicate backups and recovery processes.
  • ACID Compliance
    Although MySQL supports ACID compliance, certain configurations or storage engines may not fully adhere to ACID properties, affecting transaction reliability.
  • Concurrent Writes
    Handling a high number of concurrent writes can be less efficient compared to some other database systems designed specifically for high concurrency.
  • Feature Set
    Some advanced features found in other SQL databases (e.g., full-text indexing, rich analytics) may be less robust or absent.
  • Vendor Dependency
    With Oracle now owning MySQL, there can be concerns about licensing changes or other forms of vendor lock-in.
  • Replication Complexities
    Setting up replication and ensuring data consistency across distributed systems can be complex and error-prone.

Apache Flink features and specs

  • Real-time Stream Processing
    Apache Flink is designed for real-time data streaming, offering low-latency processing capabilities that are essential for applications requiring immediate data insights.
  • Event Time Processing
    Flink supports event time processing, which allows it to handle out-of-order events effectively and provide accurate results based on the time events actually occurred rather than when they were processed.
  • State Management
    Flink provides robust state management features, making it easier to maintain and query state across distributed nodes, which is crucial for managing long-running applications.
  • Fault Tolerance
    The framework includes built-in mechanisms for fault tolerance, such as consistent checkpoints and savepoints, ensuring high reliability and data consistency even in the case of failures.
  • Scalability
    Apache Flink is highly scalable, capable of handling both batch and stream processing workloads across a distributed cluster, making it suitable for large-scale data processing tasks.
  • Rich Ecosystem
    Flink has a rich set of APIs and integrations with other big data tools, such as Apache Kafka, Apache Hadoop, and Apache Cassandra, enhancing its versatility and ease of integration into existing data pipelines.

Possible disadvantages of Apache Flink

  • Complexity
    Flink’s advanced features and capabilities come with a steep learning curve, making it more challenging to set up and use compared to simpler stream processing frameworks.
  • Resource Intensive
    The framework can be resource-intensive, requiring substantial memory and CPU resources for optimal performance, which might be a concern for smaller setups or cost-sensitive environments.
  • Community Support
    While growing, the community around Apache Flink is not as large or mature as some other big data frameworks like Apache Spark, potentially limiting the availability of community-contributed resources and support.
  • Ecosystem Maturity
    Despite its integrations, the Flink ecosystem is still maturing, and certain tools and plugins may not be as developed or stable as those available for more established frameworks.
  • Operational Overhead
    Running and maintaining a Flink cluster can involve significant operational overhead, including monitoring, scaling, and troubleshooting, which might require a dedicated team or additional expertise.

MySQL videos

+ Add

MySQL IN 10 MINUTES (2020) | Introduction to Databases, SQL, & MySQL

More videos:

  • Review - A Review of MySQL Open Source Software

Apache Flink videos

+ Add

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 MySQL and Apache Flink)

MySQL

Apache Flink

Databases
91 91%
Databases
9% 9
Big Data
0 0%
Big Data
100% 100
Relational Databases
100 100%
Relational Databases
0% 0
Stream Processing
0 0%
Stream Processing
100% 100

User comments

Share your experience with using MySQL and Apache Flink. For example, how are they different and which one is better?
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Reviews

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

MySQL Reviews

MariaDB Vs MySQL In 2019: Compatibility, Performance, And Syntax
MySQL: MySQL is an open-source relational database management system (RDBMS). Just like all other relational databases, MySQL uses tables, constraints, triggers, roles, stored procedures and views as the core components that you work with. A table consists of rows, and each row contains a same set of columns. MySQL uses primary keys to uniquely identify each row (a.k.a...
Source: blog.panoply.io
20+ MongoDB Alternatives You Should Know About
MySQL® is another feasible replacement. MySQL 5.7 and MySQL 8 have great support for JSON, and it continues to get better with every maintenance release. You can also consider MySQL Cluster for medium size sharded environments. You can also consider MariaDB and Percona Server for MySQL
Source: www.percona.com

Apache Flink Reviews

We have no reviews of Apache Flink yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Flink should be more popular than MySQL. It has been mentiond 40 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.

MySQL mentions (4)

  • I have a recurring issue with a MySQL DB where I continually run out of disk space due to logs being filled. I've tried everything I can think of. Can anyone think of anything else I should try?
    So, I did a quick read through the mysql reference and found a bunch of flush related commands. I tried:. Source: almost 2 years ago
  • MMORPG design resources
    MySQL: Any SQL or DB knock-off, really... mysql.com - mariadb.org - sqlite.org. Source: over 2 years ago
  • Probably a syntax error
    15 years and five strokes ago. I was a Unix sysadmin. ALthough I was never an actual programmer, I did maintenance/light enhancement for the organization's website, in php. Now, as self-administered cognative therapy, I'm going back to it. This is an evil HR application that uses the mysql.com employees sample database. The module below enables the evil HR end user to generate a list of the oldest workers so... Source: almost 4 years ago
  • An absolute nightmare with mysql 8.0.25
    I always use the packages from mysql.com, that way I don't have to deal with strange configuration stuff along those lines, but anyway, I'm afraid I'm out of ideas. Surely someone else would have run in to the same issue here though. Source: almost 4 years ago

Apache Flink mentions (40)

  • Is RisingWave the Next Apache Flink?
    Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / 6 days ago
  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 11 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / 16 days ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / 23 days ago
  • Exploring the Power and Community Behind Apache Flink
    In conclusion, Apache Flink is more than a big data processing tool—it is a thriving ecosystem that exemplifies the power of open source collaboration. From its impressive technical capabilities to its innovative funding model, Apache Flink shows that sustainable software development is possible when community, corporate support, and transparency converge. As industries continue to demand efficient real-time data... - Source: dev.to / about 2 months ago
View more

What are some alternatives?

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

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

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

Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.

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

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

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

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