DBMS > DataFS vs. STSdb vs. Teradata vs. TerarkDB

System Properties Comparison DataFS vs. STSdb vs. Teradata vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A hybrid cloud data analytics software platform (Teradata Vantage)

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Graph DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

newdatabase.com

github.com/STSSoft/STSdb4

www.teradata.com

github.com/bytedance/terarkdb

Technical documentation

dev.mobiland.com/Overview.xsp

docs.teradata.com

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Mobiland AG

STS Soft SC

Teradata

ByteDance, originally Terark

Initial release

2018

2011

1984

2016

Current release

1.1.263, October 2022

4.0.8, September 2015

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

commercial

restricted open source version available

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

C++

Server operating systems

Windows

hosted
Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

.NET Client API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

C++ API
Java API

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
Java

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Windows-Profile

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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