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  1. Stackups
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  4. Databases
  5. Google Cloud Spanner vs Vitess

Google Cloud Spanner vs Vitess

OverviewComparisonAlternatives

Overview

Vitess
Vitess
Stacks66
Followers166
Votes0
Google Cloud Spanner
Google Cloud Spanner
Stacks57
Followers117
Votes3
GitHub Stars2.0K
Forks1.1K

Google Cloud Spanner vs Vitess: What are the differences?

Introduction

Google Cloud Spanner and Vitess are both popular database technologies that are used for scaling and managing large amounts of data. While they serve similar purposes, there are several key differences between the two.

  1. Scalability: Google Cloud Spanner is a globally distributed horizontally scalable relational database service, designed to scale to massive amounts of data across multiple regions. It offers linear scalability and can handle high read and write throughput. On the other hand, Vitess is a sharding middleware for MySQL databases, which enables horizontal scalability by dividing large databases into smaller, more manageable chunks called shards. It provides automatic sharding and resharding capabilities, allowing for elastic scaling of the database.

  2. Consistency Model: Cloud Spanner provides strong consistency guarantees across global transactions. It ensures that all reads see the most recent committed state of the data, regardless of the location of the read. Vitess, on the other hand, implements a more flexible consistency model called "semi-synchronous replication." It allows for asynchronous replication between shards, meaning there might be a slight delay in reading the most up-to-date data across all shards.

  3. Storage Model: Cloud Spanner uses a storage model based on external storage that provides horizontal scalability and fault tolerance. It stores data in split tablets across nodes, where each tablet contains a range of keys. Vitess, on the other hand, relies on the underlying storage engine of the MySQL database it is deployed on. It does not introduce a new storage model but rather provides sharding capabilities on top of existing MySQL storage engines.

  4. Querying Language: Cloud Spanner supports SQL query language, making it easy to interact with using familiar SQL syntax. It also supports distributed SQL queries that can span across multiple regions. Vitess, on the other hand, primarily provides compatibility with MySQL, which means it uses the MySQL query language for querying and managing data.

  5. Transaction Management: Cloud Spanner offers distributed transactions with ACID guarantees across globally distributed data. It allows for strongly consistent reads and writes across multiple regions. Vitess, on the other hand, does not provide distributed transaction support out of the box. It relies on the transactional capabilities of the underlying MySQL storage engine and does not support distributed transactions.

  6. Use Cases: Cloud Spanner is suitable for use cases that require global scalability, strong consistency, and support for transactional operations. It is often used for large-scale, globally distributed applications that need a horizontally scalable relational database. Vitess, on the other hand, is primarily used for scaling MySQL databases in a cloud-native environment. It is well-suited for sharding large databases, providing elasticity, and enabling horizontal scalability.

In summary, Google Cloud Spanner is a globally distributed horizontally scalable relational database with strong consistency and ACID transactions, whereas Vitess is a sharding middleware for MySQL databases that enables horizontal scalability using sharding techniques and is suitable for cloud-native environments.

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Detailed Comparison

Vitess
Vitess
Google Cloud Spanner
Google Cloud Spanner

It is a database solution for deploying, scaling and managing large clusters of MySQL instances. It’s architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database.

It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.

Scalability; Connection pooling; Manageability
Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars
-
GitHub Stars
2.0K
GitHub Forks
-
GitHub Forks
1.1K
Stacks
66
Stacks
57
Followers
166
Followers
117
Votes
0
Votes
3
Pros & Cons
No community feedback yet
Pros
  • 1
    Scalable
  • 1
    Horizontal scaling
  • 1
    Strongly consistent
Integrations
Amazon RDS
Amazon RDS
Kubernetes
Kubernetes
MySQL
MySQL
MySQL
MySQL
PostgreSQL
PostgreSQL
MongoDB
MongoDB
SQLite
SQLite

What are some alternatives to Vitess, Google Cloud Spanner?

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.

MySQL

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

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.

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