DBMS > Kinetica vs. STSdb vs. TimesTen vs. TinkerGraph

System Properties Comparison Kinetica vs. STSdb vs. TimesTen vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	0.08
Rank	#345	Overall
	#34	Graph DBMS

Website

www.kinetica.com

github.com/STSSoft/STSdb4

www.oracle.com/database/technologies/related/timesten.html

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.kinetica.com

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Kinetica

STS Soft SC

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2011

1998

2009

Current release

7.1, August 2021

4.0.8, September 2015

Release 22.1

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

commercial

Open Source

Apache 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

C, C++

Java

Server operating systems

Linux

Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

TinkerPop 3

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C#
Java

C
C++
Java
Node.js
PL/SQL
Python

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

PL/SQL

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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 or Eventual Consistency depending on configuration

none

Foreign keys

Referential integrity

yes

Relationships in graphs

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

by means of logfiles and checkpoints

optional

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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