DBMS > Derby vs. Lovefield vs. Quasardb vs. Teradata Aster vs. VoltDB

System Properties Comparison Derby vs. Lovefield vs. Quasardb vs. Teradata Aster vs. VoltDB

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Embeddable relational database for web apps written in pure JavaScript

Distributed, high-performance timeseries database

Platform for big data analytics on multistructured data sources and types

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

db.apache.org/derby

google.github.io/lovefield

quasar.ai

www.voltdb.com

Technical documentation

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

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

doc.quasar.ai/master

docs.voltdb.com

Developer

Apache Software Foundation

Google

quasardb

Teradata

VoltDB Inc.

Initial release

1997

2014

2009

2005

2010

Current release

10.17.1.0, November 2023

2.1.12, February 2017

3.14.1, January 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

JavaScript

C++

Java, C++

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

BSD
Linux
OS X
Windows

Linux

Linux
OS X

for development

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

in Aster File Store

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

JDBC

HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java

JavaScript

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C#
C++
Java
Python
R

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

R packages

Java

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication with selectable replication factor

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

SQL Map-Reduce Framework

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

by using LevelDB

yes

Snapshots and command logging

In-memory capabilities

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

yes

using MemoryDB

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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