DBMS > Amazon Neptune vs. Blazegraph vs. HugeGraph vs. LeanXcale vs. Oracle Berkeley DB

System Properties Comparison Amazon Neptune vs. Blazegraph vs. HugeGraph vs. LeanXcale vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

Fast, reliable graph database built for the cloud

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

A fast-speed and highly-scalable Graph DBMS

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Widely used in-process key-value store

Primary database model

Graph DBMS
RDF store

Graph DBMS

Key-value store
Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

aws.amazon.com/neptune

blazegraph.com

github.com/hugegraph
hugegraph.apache.org

www.leanxcale.com

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

Technical documentation

aws.amazon.com/neptune/developer-resources

wiki.blazegraph.com

hugegraph.apache.org/docs

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Amazon

Blazegraph

Baidu

LeanXcale

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2017

2006

2018

2015

1994

Current release

2.1.5, March 2019

0.9

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Apache Version 2.0

commercial

Open Source

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

Java

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Unix

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

only with the Berkeley DB XML edition

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SPARQL is used as query language

yes

through Apache Derby

yes

SQL interfaced based on SQLite is available

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Groovy
Java
Python

C
Java
Scala

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

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

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.

yes

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

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in Graphs

yes

edges in graph

yes

Transaction concepts

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

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.

yes

User concepts

Access control

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Users, roles and permissions

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