DBMS > Amazon Neptune vs. H2 vs. LeanXcale vs. Riak TS

System Properties Comparison Amazon Neptune vs. H2 vs. LeanXcale vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

aws.amazon.com/neptune

www.h2database.com

www.leanxcale.com

Technical documentation

aws.amazon.com/neptune/developer-resources

www.h2database.com/html/main.html

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

Developer

Amazon

Thomas Mueller

LeanXcale

Open Source, formerly Basho Technologies

Initial release

2017

2005

2015

Current release

2.2.220, July 2023

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

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

Erlang

Server operating systems

hosted

All OS with a Java VM

Linux
OS X

Data scheme

schema-free

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

yes

through Apache Derby

yes, limited

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP API
Native Erlang Interface

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java

C
Java
Scala

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

Java Stored Procedures and User-Defined Functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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.

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

links between datasets 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

yes, multi-version concurrency control (MVCC)

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)

fine grained access rights according to SQL-standard

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