DBMS > Atos Standard Common Repository vs. GridGain vs. Riak TS vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. GridGain vs. Riak TS vs. Snowflake

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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

GridGain is an in-memory computing platform, built on Apache Ignite

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Document store
Key-value store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

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

www.gridgain.com

www.snowflake.com

Technical documentation

www.gridgain.com/docs/index.html

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

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

GridGain Systems, Inc.

Open Source, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2016

2007

2015

2014

Current release

1703

GridGain 8.5.1

3.0.0, September 2022

License

Commercial or Open Source

commercial

commercial, open source

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net, Python, REST, SQL

Erlang

Server operating systems

Linux

Linux
OS X
Solaris
Windows
z/OS

Linux
OS X

hosted

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

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

Typing

predefined data types such as float or date

optional

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

restricted

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes, limited

yes

APIs and other access methods

LDAP

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

C#
C++
Java
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Erlang

user defined functions

Triggers

yes

yes (cache interceptors and events)

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

Role-based access control
Security Hooks for custom implementations

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

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