Azure Cosmos DB vs TiDB

Overview

Azure Cosmos DB

Stacks594

Followers1.1K

Votes130

TiDB

Stacks76

Followers177

Votes28

GitHub Stars39.3K

Forks6.0K

Azure Cosmos DB vs TiDB: What are the differences?

Data Model: Azure Cosmos DB is a globally distributed, multi-model database service that supports document, key-value, graph, and column-family data models, offering flexibility in data storage. On the other hand, TiDB is a distributed NewSQL database that is designed specifically for online transaction processing (OLTP) and online analytical processing (OLAP) workloads, focusing on horizontal scalability and high performance for relational data.
Consistency Model: Azure Cosmos DB provides five levels of consistency - strong, bounded staleness, session, consistent prefix, and eventual consistency, allowing users to choose the appropriate consistency level based on their application requirements. TiDB offers strong consistency by default, ensuring that all data reads return the most recent write, which is crucial for applications with strict consistency requirements.
Storage Engine: Azure Cosmos DB utilizes SSD storage and a variety of indexing techniques to provide efficient data retrieval and query performance, making it suitable for handling diverse workloads across different data models. TiDB employs a key-value-based storage engine, TiKV, which is inspired by Google's Bigtable and HBase, optimizing storage and retrieval of structured data in a distributed environment with horizontal scalability.
SQL Support: Azure Cosmos DB offers native support for SQL queries across different data models, allowing users to write queries using SQL-like syntax for retrieving and manipulating data efficiently. In contrast, TiDB supports the MySQL protocol and SQL syntax, enabling seamless integration with existing MySQL tools and applications without the need for extensive modifications or rewrites.
Scaling: Azure Cosmos DB provides elastic scalability and automatic sharding of data across multiple regions, ensuring high availability and low latency for global applications, with the ability to adjust throughput and storage dynamically based on workload demands. TiDB enables horizontal scaling by adding more nodes to the cluster, distributing data and query processing across multiple instances to handle increasing data volumes and user concurrency effectively.
Consolidation of Workloads: Azure Cosmos DB is designed to handle a wide range of workloads, including transactional, analytical, and operational tasks, making it a versatile choice for organizations with complex data processing needs. TiDB focuses on consolidating OLTP and OLAP workloads on a single platform, simplifying the architecture and management of transactional and analytical databases for enhanced performance and cost-effectiveness.

In Summary, Azure Cosmos DB and TiDB differ in their data models, consistency models, storage engines, SQL support, scaling capabilities, and consolidation of workloads.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Detailed Comparison

Azure Cosmos DB	TiDB
Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.	Inspired by the design of Google F1, TiDB supports the best features of both traditional RDBMS and NoSQL.
Fully managed with 99.99% Availability SLA;Elastically and highly scalable (both throughput and storage);Predictable low latency: <10ms @ P99 reads and <15ms @ P99 fully-indexed writes;Globally distributed with multi-region replication;Rich SQL queries over schema-agnostic automatic indexing;JavaScript language integrated multi-record ACID transactions with snapshot isolation;Well-defined tunable consistency models: Strong, Bounded Staleness, Session, and Eventual	Horizontal scalability;Asynchronous schema changes;Consistent distributed transactions;Compatible with MySQL protocol;Written in Go;NewSQL over TiKV;Multiple storage engine support
Statistics
GitHub Stars -	GitHub Stars 39.3K
GitHub Forks -	GitHub Forks 6.0K
Stacks 594	Stacks 76
Followers 1.1K	Followers 177
Votes 130	Votes 28
Pros & Cons
Pros 28 Best-of-breed NoSQL features 22 High scalability 15 Globally distributed 14 Automatic indexing over flexible json data model 10 Tunable consistency Cons 18 Pricing 4 Poor No SQL query support	Pros 9 Open source 7 Horizontal scalability 5 Strong ACID 3 HTAP 2 Mysql Compatibility
Integrations
Azure Machine Learning MongoDB Hadoop Java Azure Functions Azure Container Service Azure Storage Azure Websites Apache Spark Python	No integrations available

What are some alternatives to Azure Cosmos DB, TiDB?

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.

Amazon DynamoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

Related Comparisons

Azure Cosmos DB vs TiDB: What are the differences?

Data Model: Azure Cosmos DB is a globally distributed, multi-model database service that supports document, key-value, graph, and column-family data models, offering flexibility in data storage. On the other hand, TiDB is a distributed NewSQL database that is designed specifically for online transaction processing (OLTP) and online analytical processing (OLAP) workloads, focusing on horizontal scalability and high performance for relational data.
Consistency Model: Azure Cosmos DB provides five levels of consistency - strong, bounded staleness, session, consistent prefix, and eventual consistency, allowing users to choose the appropriate consistency level based on their application requirements. TiDB offers strong consistency by default, ensuring that all data reads return the most recent write, which is crucial for applications with strict consistency requirements.
Storage Engine: Azure Cosmos DB utilizes SSD storage and a variety of indexing techniques to provide efficient data retrieval and query performance, making it suitable for handling diverse workloads across different data models. TiDB employs a key-value-based storage engine, TiKV, which is inspired by Google's Bigtable and HBase, optimizing storage and retrieval of structured data in a distributed environment with horizontal scalability.
SQL Support: Azure Cosmos DB offers native support for SQL queries across different data models, allowing users to write queries using SQL-like syntax for retrieving and manipulating data efficiently. In contrast, TiDB supports the MySQL protocol and SQL syntax, enabling seamless integration with existing MySQL tools and applications without the need for extensive modifications or rewrites.
Scaling: Azure Cosmos DB provides elastic scalability and automatic sharding of data across multiple regions, ensuring high availability and low latency for global applications, with the ability to adjust throughput and storage dynamically based on workload demands. TiDB enables horizontal scaling by adding more nodes to the cluster, distributing data and query processing across multiple instances to handle increasing data volumes and user concurrency effectively.
Consolidation of Workloads: Azure Cosmos DB is designed to handle a wide range of workloads, including transactional, analytical, and operational tasks, making it a versatile choice for organizations with complex data processing needs. TiDB focuses on consolidating OLTP and OLAP workloads on a single platform, simplifying the architecture and management of transactional and analytical databases for enhanced performance and cost-effectiveness.

In Summary, Azure Cosmos DB and TiDB differ in their data models, consistency models, storage engines, SQL support, scaling capabilities, and consolidation of workloads.

Azure Cosmos DB vs TiDB

Overview