DBMS > Bangdb vs. SiteWhere vs. Solr vs. TempoIQ

System Properties Comparison Bangdb vs. SiteWhere vs. Solr vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

M2M integration platform for persisting/querying time series data

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Search engine

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

bangdb.com

github.com/sitewhere/sitewhere

solr.apache.org

tempoiq.com (offline)

Technical documentation

docs.bangdb.com

sitewhere1.sitewhere.io/index.html

solr.apache.org/resources.html

Developer

Sachin Sinha, BangDB

SiteWhere

Apache Software Foundation

TempoIQ

Initial release

2012

2010

2006

2012

Current release

BangDB 2.0, October 2021

9.6.1, May 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java

Server operating systems

Linux

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: string, long, double, int, geospatial, stream, events

yes

supports customizable data types and automatic typing

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

secondary, composite, nested, reverse, geospatial

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

Solr Parallel SQL Interface

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP REST

Java API
RESTful HTTP/JSON API

HTTP API

Supported programming languages

C
C#
C++
Java
Python

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Java plugins

Triggers

yes, Notifications (with Streaming only)

yes

User configurable commands triggered on index changes

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Users with fine-grained authorization concept

yes

simple authentication-based access control

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More resources

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4 February 2013, Paul Andlinger

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