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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. TiDB vs Vitess

TiDB vs Vitess

OverviewComparisonAlternatives

Overview

TiDB
TiDB
Stacks76
Followers177
Votes28
GitHub Stars39.3K
Forks6.0K
Vitess
Vitess
Stacks66
Followers166
Votes0

TiDB vs Vitess: What are the differences?

Key Differences between TiDB and Vitess

TiDB and Vitess are both distributed database systems that offer various features to handle large-scale workloads. However, there are significant differences between them that make each system suitable for different use cases.

  1. Architecture: TiDB is a NewSQL database that combines the strengths of traditional relational databases and NoSQL systems. It is a horizontally scalable, distributed database with a shared nothing architecture. On the other hand, Vitess is a database clustering system specifically designed for scaling MySQL horizontally. It routes queries to the appropriate MySQL shard and provides transparent sharding and connection pooling capabilities.

  2. Language Support: TiDB supports SQL and provides a full-featured SQL layer compatible with MySQL. It also allows users to perform distributed transactions across multiple machines. In contrast, Vitess is primarily designed for MySQL compatibility and supports a subset of the SQL standard. It offers additional functionalities such as schema management and the ability to stream database changes to external systems.

  3. Consistency Model: TiDB uses the strong consistency model, ensuring that all replicas are always up-to-date before committing a transaction. It maintains strict data consistency but might have a higher latency compared to systems with relaxed consistency guarantees. On the other hand, Vitess provides eventual consistency by default, allowing for higher write throughput and lower latency at the cost of potential read staleness.

  4. Data Replication: TiDB supports both synchronous and asynchronous data replication. It uses the Raft consensus algorithm to ensure data consistency and fault tolerance. Additionally, it allows users to configure replication across data centers. In contrast, Vitess uses a two-phase commit protocol to replicate data across MySQL shards. It supports both synchronous and semi-synchronous replication but does not have built-in support for cross-data center replication.

  5. Query Optimization: TiDB uses a cost-based optimizer that collects statistics about table data and generates execution plans based on this information. It can efficiently optimize complex SQL queries by considering various factors such as index selection and join order. Vitess, on the other hand, relies on MySQL's query optimizer for query optimization. It does not perform query rewriting or optimization at the same level as TiDB.

  6. Supported Use Cases: TiDB is well-suited for use cases that require strong consistency, high availability, and scalability. It is widely used in scenarios such as real-time analytics, online transaction processing (OLTP), and hybrid transactional/analytical processing (HTAP). Vitess, on the other hand, is primarily used for scaling MySQL workloads horizontally and is commonly deployed in large-scale web applications that require high write throughput and read scalability.

In summary, while both TiDB and Vitess are distributed database systems, they have key differences in architecture, language support, consistency model, data replication, query optimization, and supported use cases. TiDB offers a more comprehensive SQL layer, stronger consistency guarantees, and better support for distributed transactions, making it suitable for a wide range of use cases. On the other hand, Vitess is specifically designed for scaling MySQL horizontally and provides efficient sharding and connection pooling capabilities, making it ideal for high write throughput and read scalability in web applications.

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Detailed Comparison

TiDB
TiDB
Vitess
Vitess

Inspired by the design of Google F1, TiDB supports the best features of both traditional RDBMS and NoSQL.

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.

Horizontal scalability;Asynchronous schema changes;Consistent distributed transactions;Compatible with MySQL protocol;Written in Go;NewSQL over TiKV;Multiple storage engine support
Scalability; Connection pooling; Manageability
Statistics
GitHub Stars
39.3K
GitHub Stars
-
GitHub Forks
6.0K
GitHub Forks
-
Stacks
76
Stacks
66
Followers
177
Followers
166
Votes
28
Votes
0
Pros & Cons
Pros
  • 9
    Open source
  • 7
    Horizontal scalability
  • 5
    Strong ACID
  • 3
    HTAP
  • 2
    Enterprise Support
No community feedback yet
Integrations
No integrations available
Amazon RDS
Amazon RDS
Kubernetes
Kubernetes
MySQL
MySQL

What are some alternatives to TiDB, Vitess?

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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