DBMS > Amazon Redshift vs. Datomic vs. HEAVY.AI vs. InterSystems Caché vs. Tibero

System Properties Comparison Amazon Redshift vs. Datomic vs. HEAVY.AI vs. InterSystems Caché vs. Tibero

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A multi-model DBMS and application server

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Website

aws.amazon.com/redshift

www.datomic.com

github.com/heavyai/heavydb
www.heavy.ai

www.intersystems.com/products/cache

us.tmaxsoft.com/products/tibero

Technical documentation

docs.aws.amazon.com/redshift

docs.datomic.com

docs.heavy.ai

docs.intersystems.com

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

Developer

Amazon (based on PostgreSQL)

Cognitect

HEAVY.AI, Inc.

InterSystems

TmaxSoft

Initial release

2012

2016

1997

2003

Current release

1.0.6735, June 2023

5.10, January 2022

2018.1.4, May 2020

6, April 2015

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2; enterprise edition 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

Java, Clojure

C++ and CUDA

C and Assembler

Server operating systems

hosted

All OS with a Java VM

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

depending on used data model

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

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

All languages supporting JDBC/ODBC/Thrift
Python

C#
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

Transaction Functions

yes

Persistent Stored Procedure (PSM)

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

Round robin

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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

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