DBMS > Amazon Redshift vs. Apache Impala vs. JanusGraph vs. TerarkDB vs. Tibero

System Properties Comparison Amazon Redshift vs. Apache Impala vs. JanusGraph vs. TerarkDB 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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

janusgraph.org

github.com/bytedance/terarkdb

us.tmaxsoft.com/products/tibero

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

docs.janusgraph.org

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

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

Linux Foundation; originally developed as Titan by Aurelius

ByteDance, originally Terark

TmaxSoft

Initial release

2012

2013

2017

2016

2003

Current release

4.1.0, June 2022

0.6.3, February 2023

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

restricted open source version available

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

C++

Java

C++

C and Assembler

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

C++ API
Java API

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

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java
Python

C++
Java

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

yes

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

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

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