DBMS > Kinetica vs. RethinkDB vs. SQLite vs. TimesTen vs. YottaDB

System Properties Comparison Kinetica vs. RethinkDB vs. SQLite vs. TimesTen vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Widely used embeddable, in-process RDBMS

In-Memory RDBMS compatible to Oracle

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

www.kinetica.com

rethinkdb.com

www.sqlite.org

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

yottadb.com

Technical documentation

docs.kinetica.com

rethinkdb.com/docs

www.sqlite.org/docs.html

docs.oracle.com/database/timesten-18.1

yottadb.com/resources/documentation

Developer

Kinetica

The Linux Foundation

since July 2017

Dwayne Richard Hipp

Oracle, TimesTen Performance Software, HP

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

YottaDB, LLC

Initial release

2012

2009

2000

1998

2001

Current release

7.1, August 2021

2.4.1, August 2020

3.45.3 (15 April 2024), April 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Public Domain

commercial

Open Source

AGPL 3.0

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++

C++

Server operating systems

Linux

Linux
OS X
Windows

server-less

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

dynamic column types

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

yes

by using the Octo plugin

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C++
Java
PL/SQL

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

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

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-document operations

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

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

yes

users and table-level permissions

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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