DBMS > AgensGraph vs. Amazon CloudSearch vs. Firebase Realtime Database vs. Google BigQuery vs. OrigoDB

System Properties Comparison AgensGraph vs. Amazon CloudSearch vs. Firebase Realtime Database vs. Google BigQuery vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

Large scale data warehouse service with append-only tables

A fully ACID in-memory object graph database

Primary database model

Graph DBMS
Relational DBMS

Search engine

Document store

Relational DBMS

Document store
Object oriented DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/cloudsearch

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

origodb.com

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/cloudsearch

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

origodb.com/docs

Developer

Bitnine Global Inc.

Amazon

Google

acquired by Google 2014

Google

Robert Friberg et al

Initial release

2016

2012

2010

2009

under the name LiveDB

Current release

2.1, December 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

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

Server operating systems

Linux
OS X
Windows

hosted

Linux
Windows

Data scheme

depending on used data model

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

APIs and other access methods

Cypher Query Language
JDBC

HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
Java
JavaScript
Python

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

user defined functions

in JavaScript

yes

Triggers

Callbacks are triggered when data changes

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

yes

automatic partitioning across Amazon Search Instance as required

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

managed transparently by AWS

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

yes

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentication via encrypted signatures

yes, based on authentication and database rules

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

Google Cloud Identity & Access Management (IAM)

Role based authorization

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