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Cassandra vs MariaDB: What are the differences?

Key Differences Between Cassandra and MariaDB

Introduction

Cassandra and MariaDB are both popular database management systems that offer different features and capabilities. Understanding the key differences between these two systems can help in making the right choice for specific use cases.

  1. Scalability: Cassandra is designed for distributed environments and offers seamless scalability. It can handle large amounts of data and supports linear scalability by adding more nodes to the cluster. On the other hand, MariaDB is designed for vertical scalability, which means it can handle increased loads by adding more resources to a single server.

  2. Data Model: Cassandra follows a NoSQL, column-oriented data model, while MariaDB follows a relational data model. Cassandra's data model is highly flexible, allowing for dynamic and unpredictable data types, and providing horizontal scalability. In contrast, MariaDB provides a structured organization of data using tables, rows, and columns, making it suitable for complex relationships and traditional SQL queries.

  3. Consistency and Availability: Cassandra is designed for high availability and eventual consistency. It employs a distributed architecture with multiple replicas which allows for high uptime but may introduce some level of data inconsistency. MariaDB focuses on maintaining strict consistency across its nodes, sacrificing availability under certain circumstances.

  4. Replication: Cassandra uses a masterless distributed architecture, where all nodes in the cluster are equal and can accept write requests. It provides seamless data replication across multiple nodes for fault tolerance and high availability. On the other hand, MariaDB follows a master-slave replication scheme, where there is a single master node for write operations and multiple slave nodes for read operations.

  5. High Performance: Cassandra is known for its high throughput and low latency characteristics. It can handle a massive number of read and write operations simultaneously. MariaDB, being a relational database, provides efficient querying capabilities with support for complex joins and transactions, but may not perform as well as Cassandra in scenarios with massive write operations or high data volumes.

  6. Suitability: Due to its distributed nature, Cassandra is commonly used for handling large-scale data systems such as social media platforms, IoT applications, and financial systems. MariaDB, being a traditional relational database, is well-suited for applications that require ACID compliance and complex data relationships, such as e-commerce platforms, content management systems, and business applications.

In Summary, Cassandra is a distributed NoSQL database with high scalability and availability, while MariaDB is a relational database with strong consistency and efficient querying capabilities. Choosing between them depends on the specific requirements and use cases of the application.

Advice on Cassandra and MariaDB
Umair Iftikhar
Technical Architect at ERP Studio · | 3 upvotes · 449.7K views
Needs advice
on
CassandraCassandraDruidDruid
and
TimescaleDBTimescaleDB

Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.

My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.

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Replies (1)
Recommends
on
MongoDBMongoDB

Hi Umair, Did you try MongoDB. We are using MongoDB on a production environment and collecting data from devices like your scenario. We have a MongoDB cluster with three replicas. Data from devices are being written to the master node and real-time dashboard UI is using the secondary nodes for read operations. With this setup write operations are not affected by read operations too.

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Maxim Ryakhovskiy
Needs advice
on
MariaDBMariaDBMongooseMongoose
and
PostgreSQLPostgreSQL

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.

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Replies (7)
Reza Malek
at Meam Software Engineering Group · | 4 upvotes · 232.8K views
Recommends
on
MongooseMongoosePostgreSQLPostgreSQL

Your requirements seem nothing special. on the other hand, MongoDB is commonly used with Node. you could use Mongo without defining a Schema, does it give you any benefits? Also, note that development speed matters. In most cases RDBMS are the best choice, Learn and use Postgres for life!

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The use case you are describing would benefit from a self-hosted headless CMS like contentful. You can also go for Strapi with a database of your choice but here you would have to host Strapi and the underlying database (if not using SQLite) yourself. If you want to use Strapi, you can ease your work by using something like PlanetSCaleDB as the backing database for Strapi.

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Nutchanon Ninyawee

SQL is not so good at query lat long out of the box. you might need to use additional tools for that like UTM coordinates or Uber's H3.

If you use mongoDB, it support 2d coordinate query out of the box.

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Recommends
on
MongooseMongoose

Any database will be a great choice for your app, which is less of a technical challenge and more about great content. Go for it, the geographical search features maybe be actually handy for you.

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Tarun Batra
Senior Software Developer at Okta · | 2 upvotes · 224.9K views
Recommends
on
MongooseMongoose

MongoDB and Mongoose are commonly used with Node.js and the use case doesn't seem to be requiring any special considerations as of now. However using MongoDB now will allow you to easily expand and modify your use case in future.

If not MongoDB, then my second choice will be PostgreSQL. It's a generic purpose database with jsonb support (if you need it) and lots of resources online. Nobody was fired for choosing PostgreSQL.

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Václav Hodek
CEO, lead developer at Localazy · | 1 upvotes · 225.3K views
Recommends
on
PostgreSQLPostgreSQL

Any database engine should work well but I vote for Postgres because of PostGIS extension that may be handy for travel related site. There's nothing special about your requirements.

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Ruslan Rayanov
Recommends

Hi, Maxim! Most likely, the site is almost ready. But we would like to share our development with you. https://falcon.web-automation.ru/ This is a constructor for web application. With it, you can create almost any site with different roles which have different levels of access to information and different functionality. The platform is managed via sql. knowing sql, you will be able to change the business logic as necessary and during further project maintenance. We will be glad to hear your feedback about the platform.

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Vinay Mehta
Needs advice
on
CassandraCassandra
and
ScyllaDBScyllaDB

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

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Replies (4)
Recommends
on
ScyllaDBScyllaDB

Scylla can handle 1M/s events with a simple data model quite easily. The api to query is CQL, we have REST api but that's for control/monitoring

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Alex Peake
Recommends
on
CassandraCassandra

Cassandra is quite capable of the task, in a highly available way, given appropriate scaling of the system. Remember that updates are only inserts, and that efficient retrieval is only by key (which can be a complex key). Talking of keys, make sure that the keys are well distributed.

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Pankaj Soni
Chief Technical Officer at Software Joint · | 2 upvotes · 161.6K views
Recommends
on
CassandraCassandra

i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra

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Recommends
on
ScyllaDBScyllaDB

By 55M do you mean 55 million entity changes per 2 minutes? It is relatively high, means almost 460k per second. If I had to choose between Scylla or Cassandra, I would opt for Scylla as it is promising better performance for simple operations. However, maybe it would be worth to consider yet another alternative technology. Take into consideration required consistency, reliability and high availability and you may realize that there are more suitable once. Rest API should not be the main driver, because you can always develop the API yourself, if not supported by given technology.

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Decisions about Cassandra and MariaDB
Micha Mailänder
CEO & Co-Founder at Dechea · | 14 upvotes · 85.9K views

Fauna is a serverless database where you store data as JSON. Also, you have build in a HTTP GraphQL interface with a full authentication & authorization layer. That means you can skip your Backend and call it directly from the Frontend. With the power, that you can write data transformation function within Fauna with her own language called FQL, we're getting a blazing fast application.

Also, Fauna takes care about scaling and backups (All data are sharded on three different locations on the globe). That means we can fully focus on writing business logic and don't have to worry anymore about infrastructure.

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Omran Jamal
CTO & Co-founder at Bonton Connect · | 5 upvotes · 556.3K views

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)

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Pros of Cassandra
Pros of MariaDB
  • 119
    Distributed
  • 98
    High performance
  • 81
    High availability
  • 74
    Easy scalability
  • 53
    Replication
  • 26
    Reliable
  • 26
    Multi datacenter deployments
  • 10
    Schema optional
  • 9
    OLTP
  • 8
    Open source
  • 2
    Workload separation (via MDC)
  • 1
    Fast
  • 149
    Drop-in mysql replacement
  • 100
    Great performance
  • 74
    Open source
  • 55
    Free
  • 44
    Easy setup
  • 15
    Easy and fast
  • 14
    Lead developer is "monty" widenius the founder of mysql
  • 6
    Also an aws rds service
  • 4
    Consistent and robust
  • 4
    Learning curve easy
  • 2
    Native JSON Support / Dynamic Columns
  • 1
    Real Multi Threaded queries on a table/db

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Cons of Cassandra
Cons of MariaDB
  • 3
    Reliability of replication
  • 1
    Size
  • 1
    Updates
    Be the first to leave a con

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    What is 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.

    What is 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.

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    What companies use Cassandra?
    What companies use MariaDB?
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    What tools integrate with MariaDB?

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    What are some alternatives to Cassandra and MariaDB?
    HBase
    Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
    Google Cloud Bigtable
    Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.
    Hadoop
    The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
    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.
    Couchbase
    Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
    See all alternatives