Scylla vs YugabyteDB

Overview

ScyllaDB

Stacks143

Followers197

Votes8

YugabyteDB

Stacks50

Followers114

Votes1

GitHub Stars9.9K

Forks1.2K

Scylla vs YugabyteDB: What are the differences?

Introduction:

Scylla and YugabyteDB are two popular databases known for their scalability, performance, and fault-tolerance. While both databases belong to the NoSQL family, there are several key differences between them that set them apart from each other.

Architecture: Scylla is built on Apache Cassandra's architecture and is written in C++ to optimize performance. It is a sharded database that uses consistent hashing for distributing data across nodes. In contrast, YugabyteDB is a distributed SQL database that is based on Google Spanner's design. It uses a modified version of PostgreSQL as its query layer and a distributed key-value store for storing data.
Data Model: Scylla follows the wide-column data model and is compatible with the Cassandra Query Language (CQL), allowing users to query their data using a SQL-like syntax. It supports a flexible schema, allowing column updates and addition of new columns on a per-row basis. On the other hand, YugabyteDB supports the SQL data model, including structured, semi-structured, and unstructured data. It provides full ACID transactions and supports both SQL and NoSQL APIs.
Consistency Model: Scylla provides tunable consistency, allowing users to choose between strong consistency and eventual consistency based on their application requirements. It uses the Paxos algorithm for handling consensus. YugabyteDB, on the other hand, provides strong consistency by default but also supports eventual consistency for distributed reads. It implements the Raft consensus algorithm for achieving consistency.
Deployment: Scylla can be deployed on bare-metal servers, virtual machines, or containers, and supports cloud platforms like AWS, Azure, and Google Cloud. It also provides integration with Kubernetes for container orchestration. YugabyteDB can be deployed on bare-metal servers, VMs, or containers as well. It also supports cloud platforms and provides native integration with Kubernetes.
Global Data Distribution: Scylla supports multi-data center replication, allowing users to distribute their data across multiple geographic regions for better latency and fault-tolerance. It uses Cassandra's cross-data center replication mechanism. YugabyteDB has built-in multi-region deployments, enabling users to replicate data across different regions. It provides automatic data partitioning and rebalancing to ensure data availability and fault-tolerance.
Ecosystem and Compatibility: Scylla has a strong ecosystem with libraries, drivers, and tooling that are compatible with Cassandra. It supports a wide range of data format, including JSON and Apache Avro. YugabyteDB has compatibility with PostgreSQL, which means it can seamlessly integrate with existing PostgreSQL tools, connectors, and drivers. It also has support for distributed transactions using the YSQL API.

In summary, Scylla and YugabyteDB differ in their underlying architecture, data model, consistency model, deployment options, global data distribution capabilities, and ecosystem compatibility. These key differences make each database suitable for different use cases and requirements.

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Advice on ScyllaDB, YugabyteDB

Tom

CEO at Gentlent

Jun 9, 2020

Decided

The Gentlent Tech Team made lots of updates within the past year. The biggest one being our database:

We decided to migrate our #PostgreSQL -based database systems to a custom implementation of #Cassandra . This allows us to integrate our product data perfectly in a system that just makes sense. High availability and scalability are supported out of the box.

387k views387k

Comments

Vinay

Head of Engineering

Sep 19, 2019

Needs advice

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.

174k views174k

Comments

Detailed Comparison

ScyllaDB	YugabyteDB
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.	An open-source, high-performance, distributed SQL database built for resilience and scale. Re-uses the upper half of PostgreSQL to offer advanced RDBMS features, architected to be fully distributed like Google Spanner.
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	Resilience; High Performance; Scalability; Enterprise Grade; Cloud-native; Kubernetes; PostgreSQL-compatible; Geo-Distributed; Hybrid Cloud
Statistics
GitHub Stars -	GitHub Stars 9.9K
GitHub Forks -	GitHub Forks 1.2K
Stacks 143	Stacks 50
Followers 197	Followers 114
Votes 8	Votes 1
Pros & Cons
Pros 2 Replication 1 Written in C++ 1 High availability 1 Scale up 1 Distributed	Pros 1 Compatible with the result of pg_dump
Integrations
KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark	Golang PHP Java Python Spring Boot Apache Spark Node.js C# Kubernetes Ruby

What are some alternatives to ScyllaDB, YugabyteDB?

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.

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.

Related Comparisons

Scylla vs YugabyteDB: What are the differences?

Introduction:

Architecture: Scylla is built on Apache Cassandra's architecture and is written in C++ to optimize performance. It is a sharded database that uses consistent hashing for distributing data across nodes. In contrast, YugabyteDB is a distributed SQL database that is based on Google Spanner's design. It uses a modified version of PostgreSQL as its query layer and a distributed key-value store for storing data.
Data Model: Scylla follows the wide-column data model and is compatible with the Cassandra Query Language (CQL), allowing users to query their data using a SQL-like syntax. It supports a flexible schema, allowing column updates and addition of new columns on a per-row basis. On the other hand, YugabyteDB supports the SQL data model, including structured, semi-structured, and unstructured data. It provides full ACID transactions and supports both SQL and NoSQL APIs.
Consistency Model: Scylla provides tunable consistency, allowing users to choose between strong consistency and eventual consistency based on their application requirements. It uses the Paxos algorithm for handling consensus. YugabyteDB, on the other hand, provides strong consistency by default but also supports eventual consistency for distributed reads. It implements the Raft consensus algorithm for achieving consistency.
Deployment: Scylla can be deployed on bare-metal servers, virtual machines, or containers, and supports cloud platforms like AWS, Azure, and Google Cloud. It also provides integration with Kubernetes for container orchestration. YugabyteDB can be deployed on bare-metal servers, VMs, or containers as well. It also supports cloud platforms and provides native integration with Kubernetes.
Global Data Distribution: Scylla supports multi-data center replication, allowing users to distribute their data across multiple geographic regions for better latency and fault-tolerance. It uses Cassandra's cross-data center replication mechanism. YugabyteDB has built-in multi-region deployments, enabling users to replicate data across different regions. It provides automatic data partitioning and rebalancing to ensure data availability and fault-tolerance.
Ecosystem and Compatibility: Scylla has a strong ecosystem with libraries, drivers, and tooling that are compatible with Cassandra. It supports a wide range of data format, including JSON and Apache Avro. YugabyteDB has compatibility with PostgreSQL, which means it can seamlessly integrate with existing PostgreSQL tools, connectors, and drivers. It also has support for distributed transactions using the YSQL API.

Scylla vs YugabyteDB

Overview