DBMS > DolphinDB vs. HugeGraph vs. MaxDB vs. Microsoft SQL Server vs. SAP HANA

System Properties Comparison DolphinDB vs. HugeGraph vs. MaxDB vs. Microsoft SQL Server vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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.

A fast-speed and highly-scalable Graph DBMS

A robust and reliable RDBMS optimized to run all major SAP solutions

Microsofts flagship relational DBMS

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

Primary database model

Time Series DBMS

Graph DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.dolphindb.com

github.com/hugegraph
hugegraph.apache.org

maxdb.sap.com

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

www.sap.com/products/hana.html

Technical documentation

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

hugegraph.apache.org/docs

maxdb.sap.com/documentation

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

help.sap.com/hana

Developer

DolphinDB, Inc

Baidu

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

SAP

Initial release

2018

1984

1989

2010

Current release

v2.00.4, January 2022

0.9

7.9.10.12, February 2024

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2.0

commercial

Limited community edition free

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

Linux
Windows

Linux
macOS
Unix

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

Appliance or cloud-service

Data scheme

yes

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
WebDAV

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

JDBC
ODBC

Supported programming languages

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

Groovy
Java
Python

.Net
C#
Java
Perl
PHP
Python

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

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

yes

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

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

none

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

yes

ACID

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

User concepts

Access control

Administrators, Users, Groups

Users, roles and permissions

fine grained access rights according to SQL-standard

yes

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