MariaDB vs RocksDB

Overview

MariaDB

Stacks16.5K

Followers12.8K

Votes468

GitHub Stars6.6K

Forks1.9K

RocksDB

Stacks141

Followers290

Votes11

GitHub Stars30.9K

Forks6.6K

MariaDB vs RocksDB: What are the differences?

Data Storage: MariaDB is a relational database management system that uses SQL for querying, while RocksDB is an embeddable persistent key-value store for fast storage needs. MariaDB organizes data in tables with defined relationships, whereas RocksDB stores data in key-value pairs, allowing for efficient retrieval based on keys.
ACID Compliance: MariaDB guarantees ACID (Atomicity, Consistency, Isolation, Durability) compliance for transactions, ensuring data integrity in multi-operation scenarios. RocksDB, on the other hand, prioritizes high write throughput and is optimized for scenarios where ACID compliance is not a priority.
Use Cases: MariaDB is suitable for applications that require complex queries, transactions, and structured data storage, making it ideal for traditional relational database use cases. RocksDB, being a key-value store, shines in scenarios that demand high write throughput and fast retrieval of data, such as caching layers or real-time analytics applications.
Storage Engine: MariaDB supports multiple storage engines like InnoDB, MyRocks, and others, providing flexibility in performance tuning and data storage mechanisms. RocksDB, on the contrary, is a single storage engine designed for high-performance applications that need fast and efficient data storage capabilities.
Memory Usage: MariaDB typically consumes more memory for maintaining indexes, caches, and internal data structures due to its relational nature and various storage engines. RocksDB, being a key-value store optimized for efficiency, tends to be more memory-efficient, making it suitable for environments with limited memory resources.
Community and Support: MariaDB has a larger community and extensive support ecosystem, making it easier to find resources, documentation, and assistance for troubleshooting and optimization. RocksDB, being a more specialized storage engine, may have a smaller community and limited support options compared to MariaDB.

In Summary, MariaDB is a robust relational database management system tailored for complex query and transaction environments, while RocksDB is a high-performance key-value store optimized for fast storage and retrieval needs.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on MariaDB, RocksDB

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

Feb 9, 2022

Needs adviceon

Milvus

HBase

RocksDB

I am researching different querying solutions to handle ~1 trillion records of data (in the realm of a petabyte). The data is mostly textual. I have identified a few options: Milvus, HBase, RocksDB, and Elasticsearch. I was wondering if there is a good way to compare the performance of these options (or if anyone has already done something like this). I want to be able to compare the speed of ingesting and querying textual data from these tools. Does anyone have information on this or know where I can find some? Thanks in advance!

174k views174k

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

Detailed Comparison

MariaDB	RocksDB
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.	RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.
Replication;Insert Delayed;Events;Dynamic;Columns;Full-text;Search;GIS;Locale;Settings;subqueries;Timezones;Triggers;XML;Functions;Views;SSL;Show Profile	Designed for application servers wanting to store up to a few terabytes of data on locally attached Flash drives or in RAM;Optimized for storing small to medium size key-values on fast storage -- flash devices or in-memory;Scales linearly with number of CPUs so that it works well on ARM processors
Statistics
GitHub Stars 6.6K	GitHub Stars 30.9K
GitHub Forks 1.9K	GitHub Forks 6.6K
Stacks 16.5K	Stacks 141
Followers 12.8K	Followers 290
Votes 468	Votes 11
Pros & Cons
Pros 149 Drop-in mysql replacement 100 Great performance 74 Open source 55 Free 44 Easy setup	Pros 5 Very fast 3 Made by Facebook 2 Consistent performance 1 Ability to add logic to the database layer where needed

What are some alternatives to MariaDB, RocksDB?

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

MariaDB vs RocksDB: What are the differences?

Data Storage: MariaDB is a relational database management system that uses SQL for querying, while RocksDB is an embeddable persistent key-value store for fast storage needs. MariaDB organizes data in tables with defined relationships, whereas RocksDB stores data in key-value pairs, allowing for efficient retrieval based on keys.
ACID Compliance: MariaDB guarantees ACID (Atomicity, Consistency, Isolation, Durability) compliance for transactions, ensuring data integrity in multi-operation scenarios. RocksDB, on the other hand, prioritizes high write throughput and is optimized for scenarios where ACID compliance is not a priority.
Use Cases: MariaDB is suitable for applications that require complex queries, transactions, and structured data storage, making it ideal for traditional relational database use cases. RocksDB, being a key-value store, shines in scenarios that demand high write throughput and fast retrieval of data, such as caching layers or real-time analytics applications.
Storage Engine: MariaDB supports multiple storage engines like InnoDB, MyRocks, and others, providing flexibility in performance tuning and data storage mechanisms. RocksDB, on the contrary, is a single storage engine designed for high-performance applications that need fast and efficient data storage capabilities.
Memory Usage: MariaDB typically consumes more memory for maintaining indexes, caches, and internal data structures due to its relational nature and various storage engines. RocksDB, being a key-value store optimized for efficiency, tends to be more memory-efficient, making it suitable for environments with limited memory resources.
Community and Support: MariaDB has a larger community and extensive support ecosystem, making it easier to find resources, documentation, and assistance for troubleshooting and optimization. RocksDB, being a more specialized storage engine, may have a smaller community and limited support options compared to MariaDB.

MariaDB vs RocksDB

Overview