Amazon Redshift vs MariaDB

Overview

Amazon Redshift

Stacks1.5K

Followers1.4K

Votes108

MariaDB

Stacks16.5K

Followers12.8K

Votes468

GitHub Stars6.6K

Forks1.9K

Amazon Redshift vs MariaDB: What are the differences?

Introduction

In this article, we will compare Amazon Redshift and MariaDB, two popular database management systems, and discuss their key differences.

Data Warehousing vs. Traditional Database Management
Amazon Redshift is primarily designed for data warehousing, which means it is optimized for handling large volumes of data and complex analytical queries. On the other hand, MariaDB is a traditional database management system that is more suited for general-purpose applications and transactional workloads.
Scalability and Performance
Amazon Redshift is highly scalable and can easily handle petabytes of data by using a distributed architecture and columnar storage. It also offers parallel query execution, which enables fast query performance on large datasets. MariaDB, while it can scale to some extent, may not provide the same level of scalability and performance as Redshift for large-scale data warehousing scenarios.
Managed Service vs. Self-Managed
Amazon Redshift is a fully managed service provided by Amazon Web Services (AWS). This means that AWS takes care of the underlying infrastructure, such as hardware provisioning, software patching, and backups. MariaDB, on the other hand, is a self-managed database system that requires manual configuration, maintenance, and backups.
Data Replication and High Availability
Amazon Redshift offers automatic data replication and high availability through its Multi-AZ deployment option. This ensures that data is replicated across multiple availability zones, providing better fault tolerance and disaster recovery. MariaDB also supports replication and high availability through features like master-slave replication, but it requires manual configuration and monitoring.
Pricing Model
Amazon Redshift follows a pay-as-you-go pricing model, where you pay for the resources (compute and storage) that you consume. The pricing is based on factors like the size of the cluster, the number of nodes, and the data transfer. MariaDB, being open-source software, is free to use and does not have any direct licensing costs. However, you will need to consider the cost of infrastructure and maintenance for running MariaDB in a production environment.
Ecosystem and Integrations
Amazon Redshift is tightly integrated with other AWS services, such as Amazon S3, AWS Glue, and AWS Data Pipeline. It can also easily integrate with popular business intelligence (BI) tools and analytics platforms. MariaDB has its own ecosystem of tools and connectors, but it may require more manual configuration and setup for integrations with external services and platforms.

In summary, Amazon Redshift is a highly scalable and optimized data warehousing solution that offers managed services, automatic data replication, and high performance for complex analytical queries. MariaDB, on the other hand, is a traditional database management system that is more suited for general-purpose applications, provides better control and customization, and is free to use. Choose Amazon Redshift for large-scale data warehousing and complex analytical workloads, while MariaDB is a good choice for smaller applications and transactional workloads.

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Advice on Amazon Redshift, MariaDB

Maxim

student at USI

Aug 25, 2020

Needs adviceon

Node.js

Mongoose

PostgreSQL

Hi all. I am an informatics student, and I need to realise a simple website for my friend. I am planning to realise the website using Node.js and Mongoose, since I have already done a project using these technologies. I also know SQL, and I have used PostgreSQL and MySQL previously.

The website will show a possible travel destination and local transportation. The database is used to store information about traveling, so only admin will manage the content (especially photos). While clients will see the content uploaded by the admin. I am planning to use Mongoose because it is very simple and efficient for this project. Please give me your opinion about this choice.

321k views321k

Comments

Omran

CTO & Co-founder at Bonton Connect

Jun 19, 2020

Needs advice

We actually use both Mongo and SQL databases in production. Mongo excels in both speed and developer friendliness when it comes to geospatial data and queries on the geospatial data, but we also like ACID compliance hence most of our other data (except on-site logs) are stored in a SQL Database (MariaDB for now)

582k views582k

Comments

datocrats-org

Jul 29, 2020

Needs adviceon

Amazon EC2

Tableau

PowerBI

We need to perform ETL from several databases into a data warehouse or data lake. We want to

keep raw and transformed data available to users to draft their own queries efficiently
give users the ability to give custom permissions and SSO
move between open-source on-premises development and cloud-based production environments

We want to use inexpensive Amazon EC2 instances only on medium-sized data set 16GB to 32GB feeding into Tableau Server or PowerBI for reporting and data analysis purposes.

319k views319k

Comments

Detailed Comparison

Amazon Redshift	MariaDB
It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.	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.
Optimized for Data Warehousing- It uses columnar storage, data compression, and zone maps to reduce the amount of IO needed to perform queries. Redshift has a massively parallel processing (MPP) architecture, parallelizing and distributing SQL operations to take advantage of all available resources.;Scalable- With a few clicks of the AWS Management Console or a simple API call, you can easily scale the number of nodes in your data warehouse up or down as your performance or capacity needs change.;No Up-Front Costs- You pay only for the resources you provision. You can choose On-Demand pricing with no up-front costs or long-term commitments, or obtain significantly discounted rates with Reserved Instance pricing.;Fault Tolerant- Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. All data written to a node in your cluster is automatically replicated to other nodes within the cluster and all data is continuously backed up to Amazon S3.;SQL - Amazon Redshift is a SQL data warehouse and uses industry standard ODBC and JDBC connections and Postgres drivers.;Isolation - Amazon Redshift enables you to configure firewall rules to control network access to your data warehouse cluster.;Encryption – With just a couple of parameter settings, you can set up Amazon Redshift to use SSL to secure data in transit and hardware-acccelerated AES-256 encryption for data at rest.<br>	Replication;Insert Delayed;Events;Dynamic;Columns;Full-text;Search;GIS;Locale;Settings;subqueries;Timezones;Triggers;XML;Functions;Views;SSL;Show Profile
Statistics
GitHub Stars -	GitHub Stars 6.6K
GitHub Forks -	GitHub Forks 1.9K
Stacks 1.5K	Stacks 16.5K
Followers 1.4K	Followers 12.8K
Votes 108	Votes 468
Pros & Cons
Pros 41 Data Warehousing 27 Scalable 17 SQL 14 Backed by Amazon 5 Encryption	Pros 149 Drop-in mysql replacement 100 Great performance 74 Open source 55 Free 44 Easy setup
Integrations
SQLite MySQL Oracle PL/SQL	No integrations available

What are some alternatives to Amazon Redshift, MariaDB?

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.

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.

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.

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.

Related Comparisons

Amazon Redshift vs MariaDB: What are the differences?

Introduction

In this article, we will compare Amazon Redshift and MariaDB, two popular database management systems, and discuss their key differences.

Data Warehousing vs. Traditional Database Management
Amazon Redshift is primarily designed for data warehousing, which means it is optimized for handling large volumes of data and complex analytical queries. On the other hand, MariaDB is a traditional database management system that is more suited for general-purpose applications and transactional workloads.
Scalability and Performance
Amazon Redshift is highly scalable and can easily handle petabytes of data by using a distributed architecture and columnar storage. It also offers parallel query execution, which enables fast query performance on large datasets. MariaDB, while it can scale to some extent, may not provide the same level of scalability and performance as Redshift for large-scale data warehousing scenarios.
Managed Service vs. Self-Managed
Amazon Redshift is a fully managed service provided by Amazon Web Services (AWS). This means that AWS takes care of the underlying infrastructure, such as hardware provisioning, software patching, and backups. MariaDB, on the other hand, is a self-managed database system that requires manual configuration, maintenance, and backups.
Data Replication and High Availability
Amazon Redshift offers automatic data replication and high availability through its Multi-AZ deployment option. This ensures that data is replicated across multiple availability zones, providing better fault tolerance and disaster recovery. MariaDB also supports replication and high availability through features like master-slave replication, but it requires manual configuration and monitoring.
Pricing Model
Amazon Redshift follows a pay-as-you-go pricing model, where you pay for the resources (compute and storage) that you consume. The pricing is based on factors like the size of the cluster, the number of nodes, and the data transfer. MariaDB, being open-source software, is free to use and does not have any direct licensing costs. However, you will need to consider the cost of infrastructure and maintenance for running MariaDB in a production environment.
Ecosystem and Integrations
Amazon Redshift is tightly integrated with other AWS services, such as Amazon S3, AWS Glue, and AWS Data Pipeline. It can also easily integrate with popular business intelligence (BI) tools and analytics platforms. MariaDB has its own ecosystem of tools and connectors, but it may require more manual configuration and setup for integrations with external services and platforms.

Amazon Redshift vs MariaDB

Overview

Amazon Redshift vs MariaDB: What are the differences?