DBMS > Amazon Redshift vs. Firebase Realtime Database vs. HarperDB vs. OrientDB vs. Yanza

System Properties Comparison Amazon Redshift vs. Firebase Realtime Database vs. HarperDB vs. OrientDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Multi-model DBMS (Document, Graph, Key/Value)

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

aws.amazon.com/redshift

firebase.google.com/products/realtime-database

www.harperdb.io

orientdb.org

yanza.com

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/database

docs.harperdb.io/docs

www.orientdb.com/docs/last/index.html

Developer

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

HarperDB

OrientDB LTD; CallidusCloud; SAP

Yanza

Initial release

2012

2017

2010

2015

Current release

3.1, August 2021

3.2.29, March 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache version 2

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Node.js

Java

Server operating systems

hosted

Linux
OS X

All OS with a Java JDK (>= JDK 6)

Windows

Data scheme

yes

schema-free

dynamic schema

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

yes

JSON data 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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like data manipulation statements

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

Custom Functions

since release 3.1

Java, Javascript

Triggers

Callbacks are triggered when data changes

Hooks

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

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

informational only, not enforced by the system

yes

relationship in graphs

Transaction concepts

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

ACID

yes

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access rights for users and roles

Access rights for users and roles; record level security configurable

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