Overview

MongoDB

Stacks96.6K

Followers82.0K

Votes4.1K

GitHub Stars27.7K

Forks5.7K

TiDB

Stacks76

Followers177

Votes28

GitHub Stars39.3K

Forks6.0K

MongoDB vs TiDB: What are the differences?

Introduction

MongoDB and TiDB are both popular databases used for different purposes. MongoDB is a document-oriented database, while TiDB is a distributed SQL database. Despite the similarities in being NoSQL databases, there are key differences that set them apart from each other.

ACID guarantees: MongoDB follows a flexible schema with no support for strict transactional guarantees. On the other hand, TiDB follows a traditional SQL model and provides strong ACID guarantees.
Scalability and fault tolerance: MongoDB is designed to be horizontally scalable, allowing for easy distribution of data across different nodes. However, it lacks built-in fault tolerance mechanisms and requires manual configuration. Meanwhile, TiDB is designed to be highly scalable and fault-tolerant out-of-the-box, providing automatic sharding and replication.
Consistency model: MongoDB provides eventual consistency by default, where updates to data are not immediately reflected across all replicas. In contrast, TiDB guarantees strong consistency, ensuring that all replicas immediately reflect updates.
SQL support: MongoDB uses its own query language for data manipulation and retrieval, which is based on JavaScript. On the other hand, TiDB supports the SQL query language, making it more familiar for developers who are accustomed to working with relational databases.
Indexing options: MongoDB provides a variety of indexing options, including primary, secondary, compound, and geo indexes. TiDB also offers similar indexing options, but additionally supports clustered indexes for better performance when working with large datasets.
Data model and storage engines: MongoDB supports a flexible document data model, allowing for dynamic schemas and nested data structures. It uses a default storage engine called WiredTiger, but also provides support for pluggable storage engines. In contrast, TiDB follows a relational data model and supports the TiKV storage engine, which is a distributed key-value store optimized for transactional processing.

In summary, MongoDB and TiDB differ in terms of transactional guarantees, scalability, fault tolerance, consistency model, query language support, indexing options, and data model. While MongoDB offers more flexibility and simpler scalability, TiDB provides stronger ACID guarantees, better fault tolerance, and familiar SQL query language support.

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Advice on MongoDB, TiDB

George

Student

Mar 18, 2020

Needs adviceon

PostgreSQL

Python

Django

Hello everyone,

Well, I want to build a large-scale project, but I do not know which ORDBMS to choose. The app should handle real-time operations, not chatting, but things like future scheduling or reminders. It should be also really secure, fast and easy to use. And last but not least, should I use them both. I mean PostgreSQL with Python / Django and MongoDB with Node.js? Or would it be better to use PostgreSQL with Node.js?

*The project is going to use React for the front-end and GraphQL is going to be used for the API.

Thank you all. Any answer or advice would be really helpful!

620k views620k

Comments

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

Mike

Mar 20, 2020

Needs advice

We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.

241k views241k

Comments

Detailed Comparison

MongoDB	TiDB
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.	Inspired by the design of Google F1, TiDB supports the best features of both traditional RDBMS and NoSQL.
Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS	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 27.7K	GitHub Stars 39.3K
GitHub Forks 5.7K	GitHub Forks 6.0K
Stacks 96.6K	Stacks 76
Followers 82.0K	Followers 177
Votes 4.1K	Votes 28
Pros & Cons
Pros 829 Document-oriented storage 594 No sql 554 Ease of use 465 Fast 410 High performance Cons 6 Very slowly for connected models that require joins 3 Not acid compliant 2 Proprietary query language	Pros 9 Open source 7 Horizontal scalability 5 Strong ACID 3 HTAP 2 Mysql Compatibility

What are some alternatives to MongoDB, TiDB?

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.

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.