DBMS > Derby vs. ITTIA vs. Kinetica vs. NSDb

System Properties Comparison Derby vs. ITTIA vs. Kinetica vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Edge Time Series DBMS with Real-Time Stream Processing

Fully vectorized database across both GPUs and CPUs

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

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

Technical documentation

db.apache.org/derby/manuals/index.html

docs.kinetica.com

nsdb.io/Architecture

Developer

Apache Software Foundation

ITTIA L.L.C.

Kinetica

Initial release

1997

2007

2012

2017

Current release

10.17.1.0, November 2023

8.7

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C, C++

Java, Scala

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

Linux
macOS

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API
WebSocket

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

Java

C
C++
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Java
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

User concepts

Access control

fine grained access rights according to SQL-standard

Database file passwords

Access rights for users and roles on table level

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