DBMS > Heroic vs. InterSystems Caché vs. Oracle Rdb vs. Postgres-XL

System Properties Comparison Heroic vs. InterSystems Caché vs. Oracle Rdb vs. Postgres-XL

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A multi-model DBMS and application server

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Time Series DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

github.com/spotify/heroic

www.intersystems.com/products/cache

www.oracle.com/database/technologies/related/rdb.html

www.postgres-xl.org

Technical documentation

spotify.github.io/heroic

docs.intersystems.com

www.oracle.com/database/technologies/related/rdb-doc.html

www.postgres-xl.org/documentation

Developer

Spotify

InterSystems

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2014

1997

1984

2014

since 2012, originally named StormDB

Current release

2018.1.4, May 2020

7.4.1.1, 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

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

HP Open VMS

Linux
macOS

Data scheme

schema-free

depending on used data model

Flexible Schema (defined schema, partial schema, 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

XML type, but no XML query functionality

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
C++
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

MVCC

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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