DBMS > Amazon Neptune vs. Apache Doris vs. Drizzle vs. EJDB vs. EsgynDB

System Properties Comparison Amazon Neptune vs. Apache Doris vs. Drizzle vs. EJDB vs. EsgynDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Fast, reliable graph database built for the cloud

An MPP-based analytics DBMS embracing the MySQL protocol

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

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

Primary database model

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	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Website

aws.amazon.com/neptune

doris.apache.org
github.com/apache/doris

github.com/Softmotions/ejdb

www.esgyn.cn

Technical documentation

aws.amazon.com/neptune/developer-resources

github.com/apache/doris/wiki

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

Developer

Amazon

Apache Software Foundation, originally contributed from Baidu

Drizzle project, originally started by Brian Aker

Softmotions

Esgyn

Initial release

2017

2008

2012

2015

Current release

1.2.2, February 2023

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

GPLv2

commercial

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++

C++, Java

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X

server-less

Linux

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
MySQL client

JDBC

in-process shared library

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java

C
C++
Java
PHP

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

none

Sharding

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.

none

Multi-source replication
Source-replica replication

none

Multi-source replication between multi datacenters

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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1 July 2013, Matthias Gelbmann

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