DBMS > Derby vs. Kinetica vs. Lovefield vs. YottaDB

System Properties Comparison Derby vs. Kinetica vs. Lovefield vs. YottaDB

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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.

Fully vectorized database across both GPUs and CPUs

Embeddable relational database for web apps written in pure JavaScript

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

Relational DBMS

using the Octo plugin

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

db.apache.org/derby

www.kinetica.com

google.github.io/lovefield

yottadb.com

Technical documentation

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

docs.kinetica.com

github.com/google/lovefield/blob/master/docs/spec_index.md

yottadb.com/resources/documentation

Developer

Apache Software Foundation

Kinetica

Google

YottaDB, LLC

Initial release

1997

2012

2014

2001

Current release

10.17.1.0, November 2023

7.1, August 2021

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

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

Java

C, C++

JavaScript

Server operating systems

All OS with a Java VM

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Docker
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

by using the Octo plugin

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java

C++
Java
JavaScript (Node.js)
Python

JavaScript

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

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

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

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Users and groups based on OS-security mechanisms

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