MySQL聽vs聽Apache Spark

Need advice about which tool to choose?Ask the StackShare community!

MySQL

64.9K
49.3K
+ 1
3.7K
Apache Spark

2K
2.2K
+ 1
127
Add tool

MySQL vs Apache Spark: What are the differences?

MySQL: The world's most popular open source database. The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software; Apache Spark: Fast and general engine for large-scale data processing. Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

MySQL belongs to "Databases" category of the tech stack, while Apache Spark can be primarily classified under "Big Data Tools".

"Sql" is the top reason why over 778 developers like MySQL, while over 45 developers mention "Open-source" as the leading cause for choosing Apache Spark.

MySQL and Apache Spark are both open source tools. It seems that Apache Spark with 22.5K GitHub stars and 19.4K forks on GitHub has more adoption than MySQL with 3.98K GitHub stars and 1.56K GitHub forks.

Airbnb, Uber Technologies, and Netflix are some of the popular companies that use MySQL, whereas Apache Spark is used by Uber Technologies, Slack, and Shopify. MySQL has a broader approval, being mentioned in 2994 company stacks & 3053 developers stacks; compared to Apache Spark, which is listed in 266 company stacks and 112 developer stacks.

Decisions about MySQL and Apache Spark
Kyle Harrison
Web Application Developer at Fortinet | 11 upvotes 路 159K views

MySQL has a lot of strengths working for it. It's simple and easy to set up and use. It's JSON engine is also really good these days. Mongo is also simple to setup and use, and it's speed as a document-object storage engine is first class.

Where Postgres has both beat is in it's combining of all of the features that make both MySQL and Mongo great, while adding on enterprise grade level scalability and replication. It's Postgres' stability and robustness, while still fulfilling the roles of it's contemporaries extremely well that edge Postgre for me.

See more

When I was new with web development, I was using PHP for backend and MySQL for database. But after improving my JS skills, I chosen Node.js. Because of too many reasons including npm, express, community, fast coding and etc. MongoDB is so good for using with Node.js. If your JS skills are enough good, I recommend to migrate to Node.js and MongoDB.

See more
David 脰sterreicher

Easier scalability of MongoDB prompted this migration from MySQL.

As Runtastic grew, at some point it would have outgrown our MySQL installation. We looked for a couple of alternatives and found MongoDB as a great replacement for our use case. Read how a migration of live data from one database to another worked for us.

See more
Pros of MySQL
Pros of Apache Spark
  • 789
    Sql
  • 673
    Free
  • 557
    Easy
  • 527
    Widely used
  • 484
    Open source
  • 180
    High availability
  • 158
    Cross-platform support
  • 103
    Great community
  • 77
    Secure
  • 75
    Full-text indexing and searching
  • 25
    Fast, open, available
  • 14
    SSL support
  • 13
    Robust
  • 13
    Reliable
  • 8
    Enterprise Version
  • 7
    Easy to set up on all platforms
  • 1
    Easy, light, scalable
  • 1
    NoSQL access to JSON data type
  • 1
    Sequel Pro (best SQL GUI)
  • 1
    Replica Support
  • 1
    Relational database
  • 56
    Open-source
  • 45
    Fast and Flexible
  • 7
    One platform for every big data problem
  • 6
    Easy to install and to use
  • 6
    Great for distributed SQL like applications
  • 3
    Works well for most Datascience usecases
  • 2
    Machine learning libratimery, Streaming in real
  • 2
    In memory Computation
  • 0
    Interactive Query

Sign up to add or upvote prosMake informed product decisions

Cons of MySQL
Cons of Apache Spark
  • 13
    Owned by a company with their own agenda
  • 0
    Speed

Sign up to add or upvote consMake informed product decisions

What is MySQL?

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

What is Apache Spark?

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Need advice about which tool to choose?Ask the StackShare community!

What companies use MySQL?
What companies use Apache Spark?

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with MySQL?
What tools integrate with Apache Spark?

Sign up to get full access to all the tool integrationsMake informed product decisions

Blog Posts

Dec 8 2020 at 5:50PM
https://img.stackshare.io/company/93/8a444d2b7ec5dd7a4f3fc1819136e05178b964c8.png logo

DigitalOcean

GitHubMySQLMongoDB+11
2
1092
MySQLKafkaApache Spark+6
2
1303
Aug 28 2019 at 3:10AM
https://img.stackshare.io/stack/505487/default_e35b8bd5e615e01dc9b420dbd2a444fcbaeff755.png logo

Segment

PythonJavaAmazon S3+16
5
1846
What are some alternatives to MySQL and Apache Spark?
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
Oracle
Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
MariaDB
Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Microsoft SQL Server
Microsoft庐 SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
See all alternatives
Interest over time
News about Apache Spark
More news