DBMS > Amazon DynamoDB vs. Blazegraph vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. H2GIS

System Properties Comparison Amazon DynamoDB vs. Blazegraph vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. H2GIS

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Spatial extension of H2

Primary database model

Document store
Key-value store

Graph DBMS
RDF store

Document store

Key-value store
Wide column store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	0.77
Rank	#222	Overall
	#20	Graph DBMS
	#8	RDF stores

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/dynamodb

blazegraph.com

firebase.google.com/products/realtime-database

cloud.google.com/bigtable

www.h2gis.org

Technical documentation

docs.aws.amazon.com/dynamodb

wiki.blazegraph.com

firebase.google.com/docs/database

cloud.google.com/bigtable/docs

www.h2gis.org/docs/home

Developer

Amazon

Blazegraph

Google

acquired by Google 2014

Google

CNRS

Initial release

2012

2006

2012

2015

2013

Current release

2.1.5, March 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

extended commercial license available

commercial

Open Source

LGPL 3.0

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

Server operating systems

hosted

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

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

SPARQL is used as query language

yes

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Java
JavaScript
Objective-C

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

Java

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

yes

based on H2

Triggers

yes

by integration with AWS Lambda

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

based on H2

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

ACID across one or more tables within a single AWS account and region

ACID

yes

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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)

Security and Authentication via Web Application Container (Tomcat, Jetty)

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

based on H2

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