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  1. Stackups
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  4. Databases
  5. MySQL vs eXist-db

MySQL vs eXist-db

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
eXist-db
eXist-db
Stacks8
Followers17
Votes0

MySQL vs eXist-db: What are the differences?

Introduction

In this article, we will discuss the key differences between MySQL and eXist-db. Both MySQL and eXist-db are commonly used databases, but they have distinct features and functionalities that set them apart.

  1. Data Model: MySQL is a relational database management system (RDBMS) that is based on the traditional table-based data model. It uses tables to store data in rows and columns, and relationships between tables are defined using foreign keys. On the other hand, eXist-db is a native XML database that stores data in XML format. It allows for the hierarchical representation of data, making it well-suited for handling XML documents and related data.

  2. Querying Language: MySQL uses Structured Query Language (SQL) as its querying language. SQL provides a standardized way to interact with relational databases and supports a wide range of operations for data retrieval, manipulation, and management. eXist-db, on the other hand, supports a combination of XQuery, XPath, and XSLT as its querying languages. These languages are specifically designed for handling XML data and provide powerful capabilities for querying and transforming XML documents.

  3. Scalability: MySQL is known for its ability to handle large amounts of data and high traffic loads. It is designed to scale vertically by optimizing hardware resources such as CPU and memory. eXist-db, on the other hand, is designed to scale horizontally by distributing the data across multiple nodes or instances. This enables it to handle large volumes of XML data and support high-concurrency workloads.

  4. Indexing: MySQL uses various indexing techniques such as B-trees and hash indexes to optimize data retrieval and improve query performance. It supports indexing on both primary and secondary keys, allowing for efficient lookup and searching of data. eXist-db, on the other hand, uses an inverted index to index XML documents. This indexing mechanism allows for efficient querying and searching of XML data based on element and attribute values.

  5. Data Validation and Integrity: MySQL provides support for enforcing data integrity through the use of constraints such as primary keys, foreign keys, and check constraints. It also supports triggers and stored procedures, which can be used to implement complex business logic and data validation rules. eXist-db, on the other hand, offers built-in support for XML Schema validation. It validates XML documents against specified XML Schema definitions, ensuring data integrity and consistency.

  6. Full-Text Search: MySQL provides full-text search capabilities, allowing users to perform keyword-based searches within text fields. It supports various search operators and ranking algorithms to retrieve relevant results. eXist-db also supports full-text search, but with a focus on XML content. It allows for efficient querying and searching of XML documents based on textual content and XML element values.

In summary, MySQL is a relational database management system that uses SQL as its querying language, while eXist-db is a native XML database that stores data in XML format and supports XQuery, XPath, and XSLT for querying. MySQL scales vertically and uses various indexing techniques, while eXist-db scales horizontally and uses an inverted index for indexing XML documents. MySQL enforces data integrity through constraints and supports full-text search, while eXist-db provides built-in XML Schema validation and supports full-text search on XML content.

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Advice on MySQL, eXist-db

Kyle
Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

DecidedonPostGISPostGIS

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
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
Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceonMySQLMySQLPostgreSQLPostgreSQL

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
MySQL
eXist-db
eXist-db

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 known as High-performance native XML database engine and all-in-one solution for application building.

-
Native XML Database; Rich Application server; FullText indexing; NoSQL; XQuery Processor; XML processing stack; betterForm XForms integration
Statistics
GitHub Stars
11.8K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
-
Stacks
129.6K
Stacks
8
Followers
108.6K
Followers
17
Votes
3.8K
Votes
0
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
No community feedback yet
Integrations
No integrations available
Meteor
Meteor
MEAN
MEAN
Datadog
Datadog
Clever Cloud
Clever Cloud
Mongoose
Mongoose
Sails.js
Sails.js
Metabase
Metabase

What are some alternatives to MySQL, eXist-db?

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.

PostgreSQL

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

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.

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