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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. MySQL vs Scylla

MySQL vs Scylla

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
ScyllaDB
ScyllaDB
Stacks143
Followers197
Votes8

MySQL vs Scylla: What are the differences?

Introduction:

MySQL and Scylla are both popular database management systems, but they have significant differences in various aspects. Here are six key differences between MySQL and Scylla:

  1. Architecture: MySQL follows a traditional architecture known as the shared-disk model, where all nodes communicate with a central storage component. On the other hand, Scylla is built on the shared-nothing architecture, where each node operates independently with its own storage. This architecture leads to improved scalability and fault tolerance in Scylla.

  2. Data Model: MySQL uses a relational data model, allowing data to be organized into tables with defined relationships between them. Scylla, on the contrary, is based on a wide-column data model and supports a schema-less approach, where data can be stored in flexible column families. This enables better handling of unstructured and rapidly changing data in Scylla.

  3. Consistency: MySQL emphasizes immediate consistency, ensuring that all clients see the same version of data at a specific point in time. In Scylla, eventual consistency is the default, which means that different clients might observe different versions of data for a certain period. However, Scylla provides configurable tunings to adjust the level of consistency as per application requirements.

  4. Performance: Scylla is designed to deliver high performance and low latency, particularly for large-scale distributed systems. It achieves this through its memory-centric architecture that takes full advantage of RAM and solid-state drives. MySQL, though capable of handling significant workloads, may face scalability challenges when dealing with huge datasets or high traffic loads.

  5. Replication: MySQL utilizes synchronous replication, where write operations are committed to multiple nodes before being acknowledged. This ensures data durability but introduces some latency. In contrast, Scylla employs asynchronous replication, allowing faster write operations but potential data loss if a node fails before synchronizing the data.

  6. Availability: MySQL relies on a master-slave replication model for high availability, where a single master node handles writes while multiple slave nodes handle reads. If the master node fails, failover is required to promote one of the slaves as the new master. In Scylla, multi-master replication is native, allowing all nodes to handle both read and write operations, thereby eliminating the single point of failure.

In Summary, MySQL and Scylla differ in their architecture, data models, consistency models, performance characteristics, replication methods, and availability approaches. These differences make them suitable for different use cases depending on specific requirements, scalability needs, and latency sensitivities.

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Advice on MySQL, ScyllaDB

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
Erin
Erin

IT Specialist

Mar 10, 2020

Needs adviceonMicrosoft SQL ServerMicrosoft SQL ServerMySQLMySQLPostgreSQLPostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

  1. I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
668k views668k
Comments

Detailed Comparison

MySQL
MySQL
ScyllaDB
ScyllaDB

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.

ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows.

-
High availability; horizontal scalability; vertical scalability; Cassandra compatible; DynamoDB compatible; wide column; NoSQL; lightweight transactions; change data capture; workload prioritization; shard-per-core; IO scheduler; self-tuning
Statistics
GitHub Stars
11.8K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
-
Stacks
129.6K
Stacks
143
Followers
108.6K
Followers
197
Votes
3.8K
Votes
8
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
  • 2
    Replication
  • 1
    High performance
  • 1
    Written in C++
  • 1
    High availability
  • 1
    Scale up
Integrations
No integrations available
KairosDB
KairosDB
Wireshark
Wireshark
JanusGraph
JanusGraph
Grafana
Grafana
Hackolade
Hackolade
Prometheus
Prometheus
Kubernetes
Kubernetes
Datadog
Datadog
Kafka
Kafka
Apache Spark
Apache Spark

What are some alternatives to MySQL, ScyllaDB?

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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