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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. MonetDB vs MySQL vs PostgreSQL

MonetDB vs MySQL vs PostgreSQL

OverviewComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
PostgreSQL
PostgreSQL
Stacks103.0K
Followers83.9K
Votes3.6K
GitHub Stars19.0K
Forks5.2K
MonetDB
MonetDB
Stacks13
Followers35
Votes2

MonetDB vs MySQL vs PostgreSQL: What are the differences?

<MonetDB vs MySQL vs PostgreSQL>

1. **Data Storage**: MonetDB utilizes a columnar storage approach, making it suitable for read-heavy workloads with complex queries. In contrast, MySQL and PostgreSQL use traditional row storage, which is more beneficial for write-heavy applications.
   
2. **Parallelism Support**: MonetDB excels in parallel processing and can efficiently utilize multicore CPUs for query execution, leading to enhanced performance. On the other hand, while MySQL and PostgreSQL also support parallelism to some extent, they may not offer the same level of scalability as MonetDB in this aspect.

3. **Data Types**: PostgreSQL offers an extensive range of built-in data types, including support for arrays, JSON, and more, making it highly versatile for diverse data structures. In comparison, MySQL and MonetDB have a more limited array of data types available, which may impact the handling of complex data structures.

4. **ACID Compliance**: PostgreSQL and MySQL are both fully ACID-compliant, ensuring data integrity and consistency in transactions. MonetDB, however, focuses more on high-performance analytics and may prioritize speed over strict ACID compliance, which could be a consideration for applications requiring strong transaction guarantees.

5. **Indexing Capabilities**: PostgreSQL provides advanced indexing options like partial indexes, expression indexes, and more, allowing for efficient query optimization and performance tuning. While MySQL also offers a range of indexing techniques, MonetDB's indexing capabilities may be more limited in comparison, impacting query performance in certain scenarios.

6. **Community and Ecosystem**: MySQL and PostgreSQL have well-established communities with extensive documentation, support, and third-party tools, making them ideal choices for a wide range of applications. MonetDB, while growing in popularity, may have a smaller ecosystem and community support, which could be a factor to consider for long-term maintenance and scalability.

In Summary, MonetDB, MySQL, and PostgreSQL differ in data storage methods, parallelism support, data types, ACID compliance, indexing capabilities, and community ecosystems, impacting their suitability for various use cases.

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Detailed Comparison

MySQL
MySQL
PostgreSQL
PostgreSQL
MonetDB
MonetDB

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.

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.

MonetDB innovates at all layers of a DBMS, e.g. a storage model based on vertical fragmentation, a modern CPU-tuned query execution architecture, automatic and self-tuning indexes, run-time query optimization, and a modular software architecture.

Statistics
GitHub Stars
11.8K
GitHub Stars
19.0K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
5.2K
GitHub Forks
-
Stacks
129.6K
Stacks
103.0K
Stacks
13
Followers
108.6K
Followers
83.9K
Followers
35
Votes
3.8K
Votes
3.6K
Votes
2
Pros & Cons
Pros
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 490
    Open source
Cons
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes
Pros
  • 765
    Relational database
  • 511
    High availability
  • 439
    Enterprise class database
  • 383
    Sql
  • 304
    Sql + nosql
Cons
  • 10
    Table/index bloatings
Pros
  • 2
    High Performance

What are some alternatives to MySQL, PostgreSQL, MonetDB?

MongoDB

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 SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

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.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

CouchDB

CouchDB

Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

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