DBMS > Amazon DocumentDB vs. Manticore Search vs. MySQL vs. Trafodion vs. VoltDB

System Properties Comparison Amazon DocumentDB vs. Manticore Search vs. MySQL vs. Trafodion vs. VoltDB

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Multi-storage database for search, including full-text search.

Widely used open source RDBMS

Transactional SQL-on-Hadoop DBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

aws.amazon.com/documentdb

Technical documentation

aws.amazon.com/documentdb/resources

manual.manticoresearch.com

dev.mysql.com/doc

trafodion.apache.org/documentation.html

docs.voltdb.com

Developer

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation, originally developed by HP

VoltDB Inc.

Initial release

2019

2017

1995

2014

2010

Current release

6.0, February 2023

8.4.0, April 2024

2.3.0, February 2019

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

C++, Java

Java, C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X

for development

Data scheme

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, 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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

only a subset of SQL 99

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

Java Stored Procedures

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

yes, via HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic single-document operations

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

not for MyISAM storage engine

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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