DBMS > Amazon DocumentDB vs. HyperSQL vs. Lovefield vs. Microsoft SQL Server vs. OrientDB

System Properties Comparison Amazon DocumentDB vs. HyperSQL vs. Lovefield vs. Microsoft SQL Server vs. OrientDB

Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Embeddable relational database for web apps written in pure JavaScript

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

aws.amazon.com/documentdb

hsqldb.org

google.github.io/lovefield

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

orientdb.org

Technical documentation

aws.amazon.com/documentdb/resources

hsqldb.org/web/hsqlDocsFrame.html

github.com/google/lovefield/blob/master/docs/spec_index.md

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

www.orientdb.com/docs/last/index.html

Developer

Google

Microsoft

OrientDB LTD; CallidusCloud; SAP

Initial release

2019

2001

2014

1989

2010

Current release

2.7.2, June 2023

2.1.12, February 2017

SQL Server 2022, November 2022

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

JavaScript

C++

Java

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL-like query language, no joins

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC
Java

JavaScript

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java, SQL

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

Java, Javascript

Triggers

yes

Using read-only observers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

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

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

none

yes, but depending on the SQL-Server Edition

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

could be achieved with distributed queries

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

relationship in graphs

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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