DBMS > Amazon Neptune vs. Apache Druid vs. Lovefield vs. Machbase Neo

System Properties Comparison Amazon Neptune vs. Apache Druid vs. Lovefield vs. Machbase Neo

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

Primary database model

Graph DBMS
RDF store

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series 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	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Website

aws.amazon.com/neptune

druid.apache.org

google.github.io/lovefield

machbase.com

Technical documentation

aws.amazon.com/neptune/developer-resources

druid.apache.org/docs/latest/design

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

machbase.com/dbms

Developer

Amazon

Apache Software Foundation and contributors

Google

Machbase

Initial release

2017

2012

2014

2013

Current release

29.0.1, April 2024

2.1.12, February 2017

V8.0, August 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache 2.0

commercial

free test version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Server operating systems

hosted

Linux
OS X
Unix

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-less columns are supported

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

SQL

Support of SQL

SQL for querying

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

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.

yes, via HDFS, S3 or other storage engines

none

selectable replication factor

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

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

yes

volatile and lookup table

User concepts

Access control

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

simple password-based access control

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