Overview

MySQL

Stacks128.5K

Followers108.6K

Votes3.8K

GitHub Stars11.8K

Forks4.1K

Tarantool

Stacks32

Followers45

Votes9

GitHub Stars3.6K

Forks394

MySQL vs Tarantool: What are the differences?

Introduction

In this comparison, we will look at the key differences between MySQL and Tarantool, two popular database management systems.

Data Model: MySQL is a relational database that uses tables to store data, while Tarantool is a NoSQL database that uses collections of data, called spaces, to store information. This difference in data model affects how data is structured and queried in each system.
Architecture: MySQL follows a client-server architecture where the server stores and manages the database, and clients interact with it. Tarantool, on the other hand, is an in-memory database that combines the functionality of a database management system and an application server in a single process. This architecture allows for high-performance data processing.
Languages: MySQL supports SQL for querying and manipulating data, while Tarantool uses Lua for application logic and stored procedures. This difference in supported languages can influence the development process and the skillset required for working with each database system.
Replication and High Availability: MySQL offers various replication methods for achieving high availability, including master-slave and master-master replication. Tarantool, on the other hand, provides built-in support for replication, partitioning, and sharding, making it easier to scale and ensure data availability in distributed environments.
ACID Compliance: MySQL is ACID compliant, ensuring data integrity and transaction consistency, while Tarantool supports transactions within a single space but does not offer full ACID compliance across multiple spaces. This difference is crucial for applications that require strong consistency guarantees.
Use Cases: MySQL is well-suited for traditional relational database applications, such as e-commerce platforms and content management systems. In contrast, Tarantool is ideal for real-time analytics, caching, and other high-performance use cases that require low latency and high availability.

In Summary, MySQL and Tarantool differ in their data model, architecture, supported languages, replication capabilities, ACID compliance, and use cases, making each database system suitable for specific types of applications.

Advice on MySQL, Tarantool

Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

Decidedon

PostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k

Comments

Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k

Comments

Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceon

MySQL

PostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k

Comments

Detailed Comparison

MySQL	Tarantool
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.	It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications
-	Fast; Open source; Easy to use;Multiple index types: HASH, TREE, RTREE, BITSET;Asynchronous master-master replication;Authentication and access control;The database is just a C extension to the application server and can be turned off
Statistics
GitHub Stars 11.8K	GitHub Stars 3.6K
GitHub Forks 4.1K	GitHub Forks 394
Stacks 128.5K	Stacks 32
Followers 108.6K	Followers 45
Votes 3.8K	Votes 9
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 3 Performance 2 Super fast 2 Open source 1 Advanced key-value cache 1 In-memory cache
Integrations
No integrations available	Node.js Perl Java Python Golang NGINX C#

What are some alternatives to MySQL, Tarantool?

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.

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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.

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 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

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 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

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 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

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.