DBMS > Amazon Redshift vs. Apache Phoenix vs. H2 vs. RavenDB vs. Transbase

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. H2 vs. RavenDB vs. Transbase

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Open Source Operational and Transactional Enterprise NoSQL Document Database

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series 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	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

aws.amazon.com/redshift

phoenix.apache.org

www.h2database.com

ravendb.net

www.transaction.de/en/products/transbase.html

Technical documentation

docs.aws.amazon.com/redshift

phoenix.apache.org

www.h2database.com/html/main.html

ravendb.net/docs

www.transaction.de/en/products/transbase/features.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Thomas Mueller

Hibernating Rhinos

Transaction Software GmbH

Initial release

2012

2014

2005

2010

1987

Current release

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

2.2.220, July 2023

5.4, July 2022

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

AGPL version 3, commercial license available

commercial

free development license

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

C and C++

Server operating systems

hosted

Linux
Unix
Windows

All OS with a Java VM

Linux
macOS
Raspberry Pi
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language (RQL)

yes

APIs and other access methods

JDBC
ODBC

JDBC

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

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

Java

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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