DBMS > Atos Standard Common Repository vs. GigaSpaces vs. Snowflake vs. SQLite

System Properties Comparison Atos Standard Common Repository vs. GigaSpaces vs. Snowflake vs. SQLite

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Editorial information provided by DB-Engines

Name

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

Description

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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Trend Chart

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.gigaspaces.com

www.snowflake.com

www.sqlite.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.snowflake.net/manuals/index.html

www.sqlite.org/docs.html

Developer

Atos Convergence Creators

Gigaspaces Technologies

Snowflake Computing Inc.

Dwayne Richard Hipp

Initial release

2016

2000

2014

2000

Current release

1703

15.5, September 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

Public Domain

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

Java, C++, .Net

Server operating systems

Linux

Linux
macOS
Solaris
Windows

hosted

server-less

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

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

yes

dynamic column types

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

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 can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

SQL-92 is not fully supported

APIs and other access methods

LDAP

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages with LDAP bindings

.Net
C++
Java
Python
Scala

JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

yes, event driven architecture

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

via file-system locks

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

Role-based access control

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

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