DBMS > Amazon DocumentDB vs. Manticore Search vs. Microsoft SQL Server vs. ObjectBox

System Properties Comparison Amazon DocumentDB vs. Manticore Search vs. Microsoft SQL Server vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Description

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

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

Microsofts flagship relational DBMS

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Primary database model

Document store

Search engine

Relational DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS
Spatial DBMS

Time Series DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Website

aws.amazon.com/documentdb

manticoresearch.com

www.microsoft.com/en-us/sql-server

github.com/objectbox
objectbox.io

Technical documentation

aws.amazon.com/documentdb/resources

manual.manticoresearch.com

learn.microsoft.com/en-US/sql/sql-server

docs.objectbox.io

Developer

Manticore Software

Microsoft

ObjectBox Limited

Initial release

2019

2017

1989

2017

Current release

6.0, February 2023

SQL Server 2022, November 2022

4.0 (May 2024)

License

Commercial or Open Source

commercial

Open Source

GPL version 2

commercial

restricted free version is available

Bindings are released under Apache 2.0

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

Linux
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

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

yes, plus "flex" map-like types

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

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
OLE DB
Tabular Data Stream (TDS)

Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) 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

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

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

yes, but depending on the SQL-Server Edition

Data sync between devices allowing occasional connected databases to work completely offline

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

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

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

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

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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