DBMS > InterSystems Caché vs. Splice Machine vs. SQL.JS

System Properties Comparison InterSystems Caché vs. Splice Machine vs. SQL.JS

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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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Port of SQLite to JavaScript

Primary database model

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

www.intersystems.com/products/cache

splicemachine.com

sql.js.org

Technical documentation

docs.intersystems.com

splicemachine.com/how-it-works

sql.js.org/documentation/index.html

Developer

InterSystems

Splice Machine

Alon Zakai

enhancements implemented by others

Initial release

1997

2014

2012

Current release

2018.1.4, May 2020

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

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

JavaScript

Server operating systems

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

Linux
OS X
Solaris
Windows

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

Data scheme

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

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

.NET Client API
JDBC
ODBC
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

JavaScript API

Supported programming languages

C#
C++
Java

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

JavaScript

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

Access rights for users, groups and roles according to SQL-standard

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More resources

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