DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. EJDB vs. HugeGraph vs. Oracle vs. Trafodion

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. EJDB vs. HugeGraph vs. Oracle vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A fast-speed and highly-scalable Graph DBMS

Widely used RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

github.com/Softmotions/ejdb

github.com/hugegraph
hugegraph.apache.org

www.oracle.com/database

trafodion.apache.org

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

github.com/Softmotions/ejdb/blob/master/README.md

hugegraph.apache.org/docs

docs.oracle.com/en/database

trafodion.apache.org/documentation.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Softmotions

Baidu

Oracle

Apache Software Foundation, originally developed by HP

Initial release

2016

2012

2018

1980

2014

Current release

0.9

23c, September 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache 2.0

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

Java

C and C++

C++, Java

Server operating systems

hosted

server-less

Linux
macOS
Unix

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

in-process shared library

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Groovy
Java
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

PL/SQL

also stored procedures in Java possible

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes

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

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

yes

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

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

can be realized in PL/SQL

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

edges in graph

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

fine grained access rights according to SQL-standard

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