DBMS > Dgraph vs. EDB Postgres vs. HugeGraph vs. SAP HANA vs. Tibero

System Properties Comparison Dgraph vs. EDB Postgres vs. HugeGraph vs. SAP HANA vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

A fast-speed and highly-scalable Graph DBMS

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store
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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

dgraph.io

www.enterprisedb.com

github.com/hugegraph
hugegraph.apache.org

www.sap.com/products/hana.html

us.tmaxsoft.com/products/tibero

Technical documentation

dgraph.io/docs

www.enterprisedb.com/docs

hugegraph.apache.org/docs

help.sap.com/hana

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Dgraph Labs, Inc.

EnterpriseDB

Baidu

SAP

TmaxSoft

Initial release

2016

2005

2018

2010

2003

Current release

14, December 2021

0.9

2.0 SPS07 (April 4, 2023), April 2023

6, April 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2.0

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

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

Implementation language

Java

C and Assembler

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS
Unix

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

Groovy
Java
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

asynchronous Gremlin script jobs

SQLScript, R

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning

by hash, list or range

yes

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

yes

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication

yes

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

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

planned for next version

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Users, roles and permissions

yes

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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