DBMS > Atos Standard Common Repository vs. GridGain vs. Pinecone vs. TimesTen

System Properties Comparison Atos Standard Common Repository vs. GridGain vs. Pinecone vs. TimesTen

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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

A managed, cloud-native vector database

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Key-value store

Key-value store
Relational DBMS

Vector DBMS

Relational DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

www.gridgain.com

www.pinecone.io

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.gridgain.com/docs/index.html

docs.pinecone.io/docs/overview

docs.oracle.com/database/timesten-18.1

Developer

Atos Convergence Creators

GridGain Systems, Inc.

Pinecone Systems, Inc

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2007

2019

1998

Current release

1703

GridGain 8.5.1

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

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
OS X
Solaris
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

yes

String, Number, Boolean

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

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

yes

APIs and other access methods

LDAP

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

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages with LDAP bindings

C#
C++
Java
PHP
Python
Ruby
Scala

Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

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

PL/SQL

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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