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

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

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.

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)

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/sitewhere/sitewhere

solr.apache.org

tempoiq.com (offline)

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

sitewhere1.sitewhere.io/index.html

solr.apache.org/resources.html

www.xtdb.com/docs

Developer

Drizzle project, originally started by Brian Aker

SiteWhere

Apache Software Foundation

TempoIQ

Juxt Ltd.

Initial release

2008

2010

2006

2012

2019

Current release

7.2.4, September 2012

9.6.0, April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache Version 2

commercial

Open Source

MIT License

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

Clojure

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Windows

All OS with a Java VM

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

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

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

yes, extensible-data-notation format

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

yes

SQL

Support of SQL

yes

with proprietary extensions

Solr Parallel SQL Interface

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC

HTTP REST

Java API
RESTful HTTP/JSON API

HTTP API

HTTP REST
JDBC

Supported programming languages

C
C++
Java
PHP

.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

Clojure
Java

Server-side scripts

Stored procedures

Java plugins

Triggers

hooks for callbacks inside the server can be used.

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

yes

yes, each node contains all data

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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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