DBMS > Atos Standard Common Repository vs. InterSystems Caché vs. Snowflake vs. STSdb vs. TimescaleDB

System Properties Comparison Atos Standard Common Repository vs. InterSystems Caché vs. Snowflake vs. STSdb vs. TimescaleDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A multi-model DBMS and application server

Cloud-based data warehousing service for structured and semi-structured data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Key-value store

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Document store

Relational DBMS

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.intersystems.com/products/cache

www.snowflake.com

github.com/STSSoft/STSdb4

www.timescale.com

Technical documentation

docs.intersystems.com

docs.snowflake.net/manuals/index.html

docs.timescale.com

Developer

Atos Convergence Creators

InterSystems

Snowflake Computing Inc.

STS Soft SC

Timescale

Initial release

2016

1997

2014

2011

2017

Current release

1703

2018.1.4, May 2020

4.0.8, September 2015

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

Open Source

Apache 2.0

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

Server operating systems

Linux

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

hosted

Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

depending on used data model

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

optional

yes

primitive types and user defined types (classes)

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

LDAP

.NET Client API
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

.NET Client API

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

Supported programming languages

All languages with LDAP bindings

C#
C++
Java

JavaScript (Node.js)
Python

C#
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

yes

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

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

LDAP bind authentication

Access rights for users, groups and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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