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

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

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Graph DBMS
Relational DBMS

Search engine

Document store

Relational 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

Website

bitnine.net/agensgraph

aws.amazon.com/cloudsearch

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/cloudsearch

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

Developer

Bitnine Global Inc.

Amazon

Google

acquired by Google 2014

Google

Teradata

Initial release

2016

2012

2010

2005

Current release

2.1, December 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

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

Data scheme

depending on used data model

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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.

yes

in Aster File Store

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

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
Java
JavaScript
Python

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

user defined functions

in JavaScript

R packages

Triggers

Callbacks are triggered when data changes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

managed transparently by AWS

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

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)

fine grained access rights according to SQL-standard

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