DBMS > InfinityDB vs. Lovefield vs. Newts vs. Riak KV

System Properties Comparison InfinityDB vs. Lovefield vs. Newts vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

A Java embedded Key-Value Store which extends the Java Map interface

Embeddable relational database for web apps written in pure JavaScript

Time Series DBMS based on Cassandra

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

boilerbay.com

google.github.io/lovefield

opennms.github.io/newts

Technical documentation

boilerbay.com/infinitydb/manual

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

github.com/OpenNMS/newts/wiki

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Boiler Bay Inc.

Google

OpenNMS Group

OpenSource, formerly Basho Technologies

Initial release

2002

2014

2009

Current release

4.0

2.1.12, February 2017

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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

Java

Erlang

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Linux
OS X

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

restricted

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP REST
Java API

HTTP API
Native Erlang Interface

Supported programming languages

Java

JavaScript

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Erlang

Triggers

Using read-only observers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

links between data sets can be stored

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

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

using MemoryDB

User concepts

Access control

yes, using Riak Security

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