DBMS > Amazon DocumentDB vs. DolphinDB vs. Microsoft SQL Server vs. Realm vs. UniData,UniVerse

System Properties Comparison Amazon DocumentDB vs. DolphinDB vs. Microsoft SQL Server vs. Realm vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Microsofts flagship relational DBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

aws.amazon.com/documentdb

www.dolphindb.com

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

realm.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

aws.amazon.com/documentdb/resources

docs.dolphindb.cn/en/help200/index.html

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

realm.io/docs

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

DolphinDB, Inc

Microsoft

Realm, acquired by MongoDB in May 2019

Rocket Software

Initial release

2019

2018

1989

2014

1985

Current release

v2.00.4, January 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free community version available

commercial

restricted free version is available

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux
Windows

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

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

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

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

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

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

yes

yes, but depending on the SQL-Server Edition

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

Access rights for users and roles

Administrators, Users, Groups

fine grained access rights according to SQL-standard

yes

Access rights according to SQL-standard and operating system based

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