DBMS > Amazon Neptune vs. AnzoGraph DB vs. EsgynDB vs. Firebird vs. Riak KV

System Properties Comparison Amazon Neptune vs. AnzoGraph DB vs. EsgynDB vs. Firebird vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Firebird is an open source RDBMS forked from Borland's InterBase

Distributed, fault tolerant key-value store

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

aws.amazon.com/neptune

cambridgesemantics.com/anzograph

www.esgyn.cn

www.firebirdsql.org

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

www.firebirdsql.org/en/reference-manuals

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Amazon

Cambridge Semantics

Esgyn

Firebird Foundation

OpenSource, formerly Basho Technologies

Initial release

2017

2018

2015

2000

As fork of Borland's InterBase

2009

Current release

2.3, January 2021

5.0.0, January 2024

3.2.0, December 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Initial Developer's Public License

Open Source

Apache version 2, commercial enterprise edition

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 and C++

Erlang

Server operating systems

hosted

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

yes

schema-free

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

ADO.NET
JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HTTP API
Native Erlang Interface

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

PSQL

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

none

Sharding

no "single point of failure"

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 in MPP-Cluster

Multi-source replication between multi datacenters

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

not needed in graphs

yes

links between data sets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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.

yes

User concepts

Access control

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

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

yes, using Riak Security

More information provided by the system vendor

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