DBMS > EDB Postgres vs. HugeGraph vs. Sequoiadb vs. TimesTen vs. VoltDB

System Properties Comparison EDB Postgres vs. HugeGraph vs. Sequoiadb vs. TimesTen vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

NewSQL database with distributed OLTP and SQL

In-Memory RDBMS compatible to Oracle

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Graph DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.enterprisedb.com

github.com/hugegraph
hugegraph.apache.org

www.sequoiadb.com

www.oracle.com/database/technologies/related/timesten.html

www.voltdb.com

Technical documentation

www.enterprisedb.com/docs

hugegraph.apache.org/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.oracle.com/database/timesten-18.1

docs.voltdb.com

Developer

EnterpriseDB

Baidu

Sequoiadb Ltd.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

VoltDB Inc.

Initial release

2005

2018

2013

1998

2010

Current release

14, December 2021

0.9

11 Release 2 (11.2.2.8.0)

11.3, April 2022

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2.0

Open Source

Server: AGPL; Client: Apache V2

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java, C++

Server operating systems

Linux
Windows

Linux
macOS
Unix

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

standard with numerous extensions

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

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

Java API
RESTful HTTP API
TinkerPop Gremlin

proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

Groovy
Java
Python

.Net
C++
Java
PHP
Python

C
C++
Java
PL/SQL

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

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

JavaScript

PL/SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

yes

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

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

Source-replica replication

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 or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

simple password-based access control

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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