Overview

MySQL

Stacks128.5K

Followers108.6K

Votes3.8K

GitHub Stars11.8K

Forks4.1K

Crux

Stacks7

Followers21

Votes4

Crux (open source) vs MySQL: What are the differences?

Introduction:

Crux and MySQL are both popular database management systems, but they have distinct differences that make them suitable for different use cases. Below are the key differences between Crux (open source) and MySQL.

Data Model: Crux utilizes an immutable and append-only log-oriented data model, which enables efficient data partitioning and distribution. On the other hand, MySQL follows a traditional relational database model with tables consisting of rows and columns.
Query Language: Crux employs a powerful query language called Datalog, which provides expressive capabilities to query the data stored in the system. In contrast, MySQL uses SQL as its query language, which is widely adopted and standardized in the industry.
Scalability: Crux is designed for horizontal scalability, allowing organizations to easily scale their data storage and processing needs by adding more nodes to the cluster. MySQL, although it supports some level of scalability through replication and sharding, may face challenges in scaling for extremely large datasets.
Consistency Model: Crux follows a strong consistency model, ensuring that data is always consistent across all nodes in the cluster. MySQL, on the other hand, offers different levels of consistency based on the configuration and replication setup, which can sometimes lead to inconsistencies in data.
Data Integration: Crux provides seamless integration with other data storage systems such as Apache Kafka, enabling efficient data pipelines and real-time data processing. MySQL, while capable of integrating with external systems, may require additional tools and configurations to achieve the same level of data integration.
Community Support: Crux being a relatively newer open-source project may have a smaller community compared to MySQL, which has been around for a long time and has a vast user base. This difference in community support can affect the availability of resources, documentation, and troubleshooting assistance for users.

In Summary, Crux and MySQL differ in their data model, query language, scalability, consistency model, data integration capabilities, and community support.

Advice on MySQL, Crux

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	Crux
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.	An open source document database with bitemporal graph queries. Follows an unbundled architectural approach, which means that it is assembled from highly decoupled components through the use of semi-immutable logs at the core of its design.
-	Bitemporal modeling; Schemaless; Unbundled; Apache Kafka for primary storage; Rich query support; Distributed; Enterprise support
Statistics
GitHub Stars 11.8K	GitHub Stars -
GitHub Forks 4.1K	GitHub Forks -
Stacks 128.5K	Stacks 7
Followers 108.6K	Followers 21
Votes 3.8K	Votes 4
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 1 Open & Extensible 1 Document oriented 1 Graph queries 1 Native bitemporality
Integrations
No integrations available	Kafka Java Clojure RocksDB

What are some alternatives to MySQL, Crux?

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 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.

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.