DBMS > Amazon DocumentDB vs. Bangdb vs. Microsoft SQL Server vs. SAP Adaptive Server vs. SAP HANA

System Properties Comparison Amazon DocumentDB vs. Bangdb vs. Microsoft SQL Server vs. SAP Adaptive Server vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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

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

Microsofts flagship relational DBMS

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

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

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

aws.amazon.com/documentdb

bangdb.com

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

www.sap.com/products/technology-platform/sybase-ase.html

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/documentdb/resources

docs.bangdb.com

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

help.sap.com/docs/SAP_ASE

help.sap.com/hana

Developer

Sachin Sinha, BangDB

Microsoft

SAP, Sybase

SAP

Initial release

2019

2012

1989

1987

2010

Current release

BangDB 2.0, October 2021

SQL Server 2022, November 2022

16.0

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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Implementation language

C, C++

C++

C and C++

Server operating systems

hosted

Linux

Linux
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Appliance or cloud-service

Data scheme

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

SQL like support with command line tool

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol
RESTful HTTP API

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

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Java
Python

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

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

Java and Transact-SQL

SQLScript, R

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

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

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes

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

Tunable consistency, set CAP knob accordingly

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

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, run db with in-memory only mode

yes

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

fine grained access rights according to SQL-standard

yes

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