DBMS > Kinetica vs. MySQL vs. NSDb vs. Oracle Berkeley DB vs. Transbase

System Properties Comparison Kinetica vs. MySQL vs. NSDb vs. Oracle Berkeley DB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Widely used in-process key-value store

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.kinetica.com

www.mysql.com

nsdb.io

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

www.transaction.de/en/products/transbase.html

Technical documentation

docs.kinetica.com

dev.mysql.com/doc

nsdb.io/Architecture

docs.oracle.com/cd/E17076_05/html/index.html

www.transaction.de/en/products/transbase/features.html

Developer

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Transaction Software GmbH

Initial release

2012

1995

2017

1994

1987

Current release

7.1, August 2021

8.4.0, April 2024

18.1.40, May 2020

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Open Source

commercial license available

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C, C++

C and C++

Java, Scala

C, Java, C++ (depending on the Berkeley DB edition)

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

only with the Berkeley DB XML edition

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
Scala

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

Triggers

yes

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

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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