DBMS > InterSystems Caché vs. Lovefield vs. Riak KV vs. SQream DB

System Properties Comparison InterSystems Caché vs. Lovefield vs. Riak KV vs. SQream DB

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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

A multi-model DBMS and application server

Embeddable relational database for web apps written in pure JavaScript

Distributed, fault tolerant key-value store

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

www.intersystems.com/products/cache

google.github.io/lovefield

sqream.com

Technical documentation

docs.intersystems.com

github.com/google/lovefield/blob/master/docs/spec_index.md

www.tiot.jp/riak-docs/riak/kv/latest

docs.sqream.com

Developer

InterSystems

Google

OpenSource, formerly Basho Technologies

SQream Technologies

Initial release

1997

2014

2009

2017

Current release

2018.1.4, May 2020

2.1.12, February 2017

3.2.0, December 2022

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

commercial

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

JavaScript

Erlang

C++, CUDA, Haskell, Java, Scala

Server operating systems

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

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X

Linux

Data scheme

depending on used data model

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

restricted

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

.Net
JDBC
ODBC

Supported programming languages

C#
C++
Java

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Erlang

user defined functions in Python

Triggers

yes

Using read-only observers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access rights for users, groups and roles

yes, using Riak Security

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