DBMS > Amazon Redshift vs. Apache Impala vs. RethinkDB vs. TerminusDB vs. Tibero

System Properties Comparison Amazon Redshift vs. Apache Impala vs. RethinkDB vs. TerminusDB vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store

Spatial DBMS

Document store
RDF store

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Trend Chart

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	2.84
Rank	#106	Overall
	#19	Document stores

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

rethinkdb.com

terminusdb.com

us.tmaxsoft.com/products/tibero

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

rethinkdb.com/docs

terminusdb.github.io/terminusdb/#

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

The Linux Foundation

since July 2017

DataChemist Ltd.

TmaxSoft

Initial release

2012

2013

2009

2018

2003

Current release

4.1.0, June 2022

2.4.1, August 2020

11.0.0, January 2023

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Prolog, Rust

C and Assembler

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL-like query language (WOQL)

yes

APIs and other access methods

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

All languages supporting JDBC/ODBC

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

yes

Persistent Stored Procedure (PSM)

Triggers

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Graph Partitioning

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

in-memory journaling

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

users and table-level permissions

Role-based access control

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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