DBMS > Amazon Neptune vs. EventStoreDB vs. HugeGraph vs. KairosDB vs. Lovefield

System Properties Comparison Amazon Neptune vs. EventStoreDB vs. HugeGraph vs. KairosDB vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A fast-speed and highly-scalable Graph DBMS

Distributed Time Series DBMS based on Cassandra or H2

Embeddable relational database for web apps written in pure JavaScript

Primary database model

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	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

aws.amazon.com/neptune

www.eventstore.com

github.com/hugegraph
hugegraph.apache.org

github.com/kairosdb/kairosdb

google.github.io/lovefield

Technical documentation

aws.amazon.com/neptune/developer-resources

developers.eventstore.com

hugegraph.apache.org/docs

kairosdb.github.io

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Amazon

Event Store Limited

Baidu

Google

Initial release

2017

2012

2018

2013

2014

Current release

21.2, February 2021

0.9

1.2.2, November 2018

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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

JavaScript

Server operating systems

hosted

Linux
Windows

Linux
macOS
Unix

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

yes

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Java API
RESTful HTTP API
TinkerPop Gremlin

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Groovy
Java
Python

Java
JavaScript

Node.js
PHP
Python

JavaScript

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

Sharding

based on Cassandra

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

selectable replication factor

based on Cassandra

none

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

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

Users, roles and permissions

simple password-based access control

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