DBMS > Faircom EDGE vs. Lovefield vs. Riak KV vs. SiriDB vs. Solr

System Properties Comparison Faircom EDGE vs. Lovefield vs. Riak KV vs. SiriDB vs. Solr

Editorial information provided by DB-Engines

Name

Description

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Embeddable relational database for web apps written in pure JavaScript

Distributed, fault tolerant key-value store

Open Source Time Series DBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Key-value store

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

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

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

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

www.faircom.com/products/faircom-edge

google.github.io/lovefield

siridb.com

solr.apache.org

Technical documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

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

docs.siridb.com

solr.apache.org/resources.html

Developer

FairCom Corporation

Google

OpenSource, formerly Basho Technologies

Cesbit

Apache Software Foundation

Initial release

1979

2014

2009

2017

2006

Current release

V3, October 2020

2.1.12, February 2017

3.2.0, December 2022

9.6.0, April 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

MIT License

Open Source

Apache Version 2

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

ANSI C, C++

JavaScript

Erlang

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

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

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

Numeric data

yes

supports customizable data types and automatic typing

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

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language

via JavaScript builder pattern

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

JavaScript

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

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Erlang

Java plugins

Triggers

yes

Using read-only observers

yes

pre-commit hooks and post-commit hooks

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

links between data sets can be stored

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

yes

User concepts

Access control

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes, using Riak Security

simple rights management via user accounts

yes

More information provided by the system vendor

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