DBMS > MongoDB vs. Tarantool vs. Transbase

System Properties Comparison MongoDB vs. Tarantool vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0

Document store
Relational DBMS
Spatial DBMS

with Tarantool/GIS extension

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	458.78
Rank	#5	Overall
	#1	Document stores

Score	1.81
Rank	#152	Overall
	#27	Key-value stores

Score	0.51
Rank	#274	Overall
	#126	Relational DBMS

Website

www.mongodb.com

www.tarantool.io

www.transaction.de/en/products/transbase.html

Technical documentation

docs.mongodb.com/manual

www.tarantool.io/en/doc

www.transaction.de/en/products/transbase/features.html

Developer

MongoDB, Inc

Transaction Software GmbH

Initial release

2009

2008

1987

Current release

6.0.1, August 2022

2.10.0, May 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

BSD

commercial

free development license

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

BSD
Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

string, double, decimal, uuid, integer, blob, boolean

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

Read-only SQL queries via the MongoDB Connector for BI

Full-featured ANSI SQL support

yes

APIs and other access methods

proprietary protocol using JSON

Open binary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Lua, C and SQL stored procedures

yes

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Hash sharding based on virtual buckets

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes, with SQL

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Multi-document ACID Transactions with snapshot isolation

ACID, read commited

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes, regular snapshots on disk, write ahead logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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