DBMS > Amazon Redshift vs. Apache Phoenix vs. ArangoDB vs. Blueflood vs. Hive

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. ArangoDB vs. Blueflood vs. Hive

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A scale-out RDBMS with evolutionary schema built on Apache HBase

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

Scalable TimeSeries DBMS based on Cassandra

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Search engine

Time Series DBMS

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	3.32
Rank	#90	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores
	#10	Search engines

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

phoenix.apache.org

docs.arangodb.com

github.com/rax-maas/blueflood/wiki

cwiki.apache.org/confluence/display/Hive/Home

Social network pages

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

ArangoDB Inc.

Rackspace

Apache Software Foundation

initially developed by Facebook

Initial release

2012

2014

2012

2013

2012

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.11.5, November 2023

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial license (Enterprise) available

Open Source

Apache 2.0

Open Source

Apache Version 2

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.

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux
Unix
Windows

Linux
OS X
Windows

Linux
OS X

All OS with a Java VM

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

automatically recognizes schema within a collection

predefined scheme

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

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

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JDBC

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

HTTP REST

JDBC
ODBC
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

JavaScript

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication with configurable replication factor

selectable replication factor

based on Cassandra

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

can be done with stored procedures in JavaScript

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

Transaction concepts

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

yes

Access rights for users, groups and roles

More information provided by the system vendor

Specific characteristics

Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more

Competitive advantages

Consolidation: As a native multi-model database, can be used as a full blown document...
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Typical application scenarios

Native multi-model in ArangoDB is being used for a broad range of projects across...
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Key customers

Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
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Market metrics

ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
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Licensing and pricing models

Very permissive Apache 2 License for Community Edition & commercial licenses are...
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