DBMS > Amazon Neptune vs. LeanXcale vs. openGemini vs. Oracle Berkeley DB vs. Postgres-XL

System Properties Comparison Amazon Neptune vs. LeanXcale vs. openGemini vs. Oracle Berkeley DB vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Widely used in-process key-value store

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

Primary database model

Graph DBMS
RDF store

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

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

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

aws.amazon.com/neptune

www.leanxcale.com

www.opengemini.org
github.com/openGemini

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

www.postgres-xl.org

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.opengemini.org/guide

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

www.postgres-xl.org/documentation

Developer

Amazon

LeanXcale

Huawei and openGemini community

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2017

2015

2022

1994

2014

since 2012, originally named StormDB

Current release

1.1, July 2023

18.1.40, May 2020

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

commercial license available

Open Source

Mozilla public license

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++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

SQL-like query language

yes

SQL interfaced based on SQLite is available

yes

distributed, parallel query execution

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST

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

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
Java
Scala

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

.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

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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)

Administrators and common users accounts

fine grained access rights according to SQL-standard

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