DBMS > Atos Standard Common Repository vs. Kdb vs. Newts vs. Snowflake vs. TDengine

System Properties Comparison Atos Standard Common Repository vs. Kdb vs. Newts vs. Snowflake vs. TDengine

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

Time Series DBMS based on Cassandra

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

Time Series DBMS and big data platform

Primary database model

Document store
Key-value store

Time Series DBMS
Vector DBMS

Time Series DBMS

Relational DBMS

Time Series DBMS

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

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

kx.com

opennms.github.io/newts

www.snowflake.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

code.kx.com

github.com/OpenNMS/newts/wiki

docs.snowflake.net/manuals/index.html

docs.tdengine.com

Developer

Atos Convergence Creators

Kx Systems, a division of First Derivatives plc

OpenNMS Group

Snowflake Computing Inc.

TDEngine, previously Taos Data

Initial release

2016

2000

kdb was released 2000, kdb+ in 2003

2014

2019

Current release

1703

3.6, May 2018

3.0, August 2022

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

Apache 2.0

commercial

Open Source

AGPL V3, also commercial editions available

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

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

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

yes

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'

SQL

Support of SQL

SQL-like query language (q)

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

LDAP

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP REST
Java API

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

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

Java

JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

with views

similar concept for controling cloud resources

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

Sharding

based on Cassandra

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

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

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

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

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

yes

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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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

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
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Licensing and pricing models

upon request
» more

TDengine OSS is an open source, cloud native time series database. It includes built-in...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.