DBMS > Atos Standard Common Repository vs. Axibase vs. GridGain vs. Tkrzw

System Properties Comparison Atos Standard Common Repository vs. Axibase vs. GridGain vs. Tkrzw

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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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Key-value store

Time Series DBMS

Key-value store
Relational DBMS

Key-value store

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

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

axibase.com/docs/atsd/finance

www.gridgain.com

dbmx.net/tkrzw

Technical documentation

www.gridgain.com/docs/index.html

Developer

Atos Convergence Creators

Axibase Corporation

GridGain Systems, Inc.

Mikio Hirabayashi

Initial release

2016

2013

2007

2020

Current release

1703

15585

GridGain 8.5.1

0.9.3, August 2020

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Apache Version 2.0

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

Java, C++, .Net

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language

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

APIs and other access methods

LDAP

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

Supported programming languages

All languages with LDAP bindings

Go
Java
PHP
Python
R
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

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

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

Source-replica replication

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

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

using specific database classes

User concepts

Access control

LDAP bind authentication

Security Hooks for custom implementations

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