DBMS > Drizzle vs. Geode vs. SiteWhere vs. Solr vs. TempoIQ

System Properties Comparison Drizzle vs. Geode vs. SiteWhere vs. Solr vs. TempoIQ

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Secondary database models

Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

geode.apache.org

github.com/sitewhere/sitewhere

solr.apache.org

tempoiq.com (offline)

Technical documentation

geode.apache.org/docs

sitewhere1.sitewhere.io/index.html

solr.apache.org/resources.html

Developer

Drizzle project, originally started by Brian Aker

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

SiteWhere

Apache Software Foundation

TempoIQ

Initial release

2008

2002

2010

2006

2012

Current release

7.2.4, September 2012

1.1, February 2017

9.6.0, April 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses available as Gemfire

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++

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

the JDK (8 or later) is also required

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

yes

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

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

All search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (OQL)

Solr Parallel SQL Interface

APIs and other access methods

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

HTTP REST

Java API
RESTful HTTP/JSON API

HTTP API

Supported programming languages

C
C++
Java
PHP

.Net
All JVM based languages
C++
Groovy
Java
Scala

.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

user defined functions

Java plugins

Triggers

hooks for callbacks inside the server can be used.

yes

Cache Event Listeners

yes

User configurable commands triggered on index changes

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights per client and object definable

Users with fine-grained authorization concept

yes

simple authentication-based access control

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More resources

DB-Engines blog posts

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2 July 2014, Paul Andlinger

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