DBMS > Amazon Neptune vs. Google BigQuery vs. JanusGraph vs. Speedb

System Properties Comparison Amazon Neptune vs. Google BigQuery vs. JanusGraph vs. Speedb

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Large scale data warehouse service with append-only tables

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.17
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	50.58
Rank	#19	Overall
	#13	Relational DBMS

Score	1.78
Rank	#131	Overall
	#12	Graph DBMS

Score	0.16
Rank	#318	Overall
	#46	Key-value stores

Website

aws.amazon.com/neptune

cloud.google.com/bigquery

janusgraph.org

www.speedb.io

Technical documentation

aws.amazon.com/neptune/developer-resources

cloud.google.com/bigquery/docs

docs.janusgraph.org

Developer

Amazon

Google

Linux Foundation; originally developed as Titan by Aurelius

Speedb

Initial release

2017

2010

2017

2020

Current release

1.0.0, October 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0; 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++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux
Windows

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

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Clojure
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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)

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

User authentification and security via Rexster Graph Server

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