DBMS > Atos Standard Common Repository vs. Kdb vs. Microsoft Azure Table Storage vs. Newts vs. Riak KV

System Properties Comparison Atos Standard Common Repository vs. Kdb vs. Microsoft Azure Table Storage vs. Newts vs. Riak KV

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 Time Series DBMS

A Wide Column Store for rapid development using massive semi-structured datasets

Time Series DBMS based on Cassandra

Distributed, fault tolerant key-value store

Primary database model

Document store
Key-value store

Time Series DBMS
Vector DBMS

Wide column store

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Relational DBMS

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

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

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

kx.com

azure.microsoft.com/en-us/services/storage/tables

opennms.github.io/newts

Technical documentation

code.kx.com

github.com/OpenNMS/newts/wiki

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

Developer

Atos Convergence Creators

Kx Systems, a division of First Derivatives plc

Microsoft

OpenNMS Group

OpenSource, formerly Basho Technologies

Initial release

2016

2000

kdb was released 2000, kdb+ in 2003

2012

2014

2009

Current release

1703

3.6, May 2018

3.2.0, December 2022

License

Commercial or Open Source

commercial

free 32-bit version

commercial

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

Linux

Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Linux
OS X

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

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

table attribute 'grouped'

restricted

SQL

Support of SQL

SQL-like query language (q)

APIs and other access methods

LDAP

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

RESTful HTTP API

HTTP REST
Java API

HTTP API
Native Erlang Interface

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java

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

Server-side scripts

Stored procedures

user defined functions

Erlang

Triggers

yes

with views

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

based on Cassandra

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of specific operations

optimistic locking

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

rights management via user accounts

Access rights based on private key authentication or shared access signatures

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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