DBMS > Amazon Aurora vs. Bangdb vs. DolphinDB vs. Microsoft SQL Server vs. PostGIS

System Properties Comparison Amazon Aurora vs. Bangdb vs. DolphinDB vs. Microsoft SQL Server vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Converged and high performance database for device data, events, time series, document and graph

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

Spatial extension of PostgreSQL

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Document store

Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

aws.amazon.com/rds/aurora

bangdb.com

www.dolphindb.com

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

postgis.net

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.bangdb.com

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

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

postgis.net/documentation

Developer

Amazon

Sachin Sinha, BangDB

DolphinDB, Inc

Microsoft

Initial release

2015

2012

2018

1989

2005

Current release

BangDB 2.0, October 2021

v2.00.4, January 2022

SQL Server 2022, November 2022

3.4.2, February 2024

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

free community version available

commercial

restricted free version is available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++

C++

Server operating systems

hosted

Linux

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Proprietary protocol
RESTful HTTP API

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)

Supported programming languages

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

C
C#
C++
Java
Python

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

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

Server-side scripts

Stored procedures

yes

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

user defined functions

Triggers

yes

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning

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

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor, Knob for CAP (enterprise version only)

yes

yes, but depending on the SQL-Server Edition

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

Administrators, Users, Groups

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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