DBMS > NSDb vs. RethinkDB vs. SiteWhere vs. Solr vs. SwayDB

System Properties Comparison NSDb vs. RethinkDB vs. SiteWhere vs. Solr vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

M2M integration platform for persisting/querying time series data

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

nsdb.io

rethinkdb.com

github.com/sitewhere/sitewhere

solr.apache.org

swaydb.simer.au

Technical documentation

nsdb.io/Architecture

rethinkdb.com/docs

sitewhere1.sitewhere.io/index.html

solr.apache.org/resources.html

Developer

The Linux Foundation

since July 2017

SiteWhere

Apache Software Foundation

Simer Plaha

Initial release

2017

2009

2010

2006

2018

Current release

2.4.1, August 2020

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache Version 2

Open Source

GNU Affero GPL V3.0

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, Scala

C++

Java

Scala

Server operating systems

Linux
macOS

Linux
OS X
Windows

All OS with a Java VM

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

Data scheme

schema-free

predefined scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

yes

string, binary, float, bool, date, geometry

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

all fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

Solr Parallel SQL Interface

APIs and other access methods

gRPC
HTTP REST
WebSocket

HTTP REST

Java API
RESTful HTTP/JSON API

Supported programming languages

Java
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Java plugins

Triggers

Client-side triggers through changefeeds

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Sharding

based on HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on HBase

yes

none

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-document operations

optimistic locking

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

Using Apache Lucene

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

users and table-level permissions

Users with fine-grained authorization concept

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

Meet some database management systems you are likely to hear more about in the future
4 August 2014, Paul Andlinger

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Elasticsearch replaced Solr as the most popular search engine
12 January 2016, Paul Andlinger

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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Recent citations in the news

MongoDB: The Popular Database for IoT
15 August 2023, Open Source For You

How to Use RethinkDB with Node.js Applications — SitePoint
16 December 2015, SitePoint

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5 October 2016, VentureBeat

RethinkDB is dead, and MongoDB isn't what killed it
24 January 2017, TechRepublic

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14 February 2018, Packt Hub

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