DBMS > Amazon Neptune vs. Drizzle vs. JaguarDB vs. Postgres-XL vs. WakandaDB

System Properties Comparison Amazon Neptune vs. Drizzle vs. JaguarDB vs. Postgres-XL vs. WakandaDB

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

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

Performant, highly scalable DBMS for AI and IoT applications

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

aws.amazon.com/neptune

www.jaguardb.com

www.postgres-xl.org

wakanda.github.io

Technical documentation

aws.amazon.com/neptune/developer-resources

www.jaguardb.com/support.html

www.postgres-xl.org/documentation

wakanda.github.io/doc

Developer

Amazon

Drizzle project, originally started by Brian Aker

DataJaguar, Inc.

Wakanda SAS

Initial release

2017

2008

2015

2014

since 2012, originally named StormDB

2012

Current release

7.2.4, September 2012

3.3 July 2023

10 R1, October 2018

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

GPL V3.0

Open Source

Mozilla public license

Open Source

AGPLv3, extended commercial license 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++

the server part. Clients available in other languages

C++, JavaScript

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux

Linux
macOS

Linux
OS X
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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

distributed, parallel query execution

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC

JDBC
ODBC

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

RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Java
PHP

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

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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
Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

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)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

rights management via user accounts

fine grained access rights according to SQL-standard

yes

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More resources

DB-Engines blog posts

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

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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