DBMS > Atos Standard Common Repository vs. eXtremeDB vs. Google BigQuery vs. OpenTSDB vs. Transwarp KunDB

System Properties Comparison Atos Standard Common Repository vs. eXtremeDB vs. Google BigQuery vs. OpenTSDB vs. Transwarp KunDB

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Large scale data warehouse service with append-only tables

Scalable Time Series DBMS based on HBase

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

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

www.mcobject.com

cloud.google.com/bigquery

opentsdb.net

www.transwarp.cn/en/product/kundb

Technical documentation

www.mcobject.com/docs/extremedb.htm

cloud.google.com/bigquery/docs

opentsdb.net/docs/build/html/index.html

Developer

Atos Convergence Creators

McObject

Google

currently maintained by Yahoo and other contributors

Transwarp

Initial release

2016

2001

2010

2011

Current release

1703

8.2, 2021

License

Commercial or Open Source

commercial

Open Source

LGPL

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

C and C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

numeric data for metrics, strings for tags

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

APIs and other access methods

LDAP

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

HTTP API
Telnet API

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning / sharding

none

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

selectable replication factor

based on HBase

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

based on HBase

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

More information provided by the system vendor

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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