DBMS > Amazon Neptune vs. EsgynDB vs. OrigoDB vs. Postgres-XL vs. TerarkDB

System Properties Comparison Amazon Neptune vs. EsgynDB vs. OrigoDB vs. Postgres-XL vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A fully ACID in-memory object graph database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

aws.amazon.com/neptune

www.esgyn.cn

origodb.com

www.postgres-xl.org

github.com/bytedance/terarkdb

Technical documentation

aws.amazon.com/neptune/developer-resources

origodb.com/docs

www.postgres-xl.org/documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Amazon

Esgyn

Robert Friberg et al

ByteDance, originally Terark

Initial release

2017

2015

2009

under the name LiveDB

2014

since 2012, originally named StormDB

2016

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

commercial

restricted open source version available

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

C++, Java

C++

Server operating systems

hosted

Linux

Linux
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

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

C++ API
Java API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication between multi datacenters

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

depending on model

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

Write ahead log

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Role based authorization

fine grained access rights according to SQL-standard

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