DBMS > Amazon Redshift vs. Solr vs. SWC-DB vs. TempoIQ vs. VoltDB

System Properties Comparison Amazon Redshift vs. Solr vs. SWC-DB vs. TempoIQ vs. VoltDB

Editorial information provided by DB-Engines

Name

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

Description

Large scale data warehouse service for use with business intelligence tools

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

A high performance, scalable Wide Column DBMS

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

aws.amazon.com/redshift

solr.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

tempoiq.com (offline)

www.voltdb.com

Technical documentation

docs.aws.amazon.com/redshift

solr.apache.org/resources.html

docs.voltdb.com

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Alex Kashirin

TempoIQ

VoltDB Inc.

Initial release

2012

2006

2020

2012

2010

Current release

9.6.1, May 2024

0.5, April 2021

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPL V3

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

C++

Java, C++

Server operating systems

hosted

All OS with a Java VM

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

Linux

Linux
OS X

for development

Data scheme

yes

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

schema-free

yes

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

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Solr Parallel SQL Interface

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

Proprietary protocol
Thrift

HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

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

C++

C#
Java
JavaScript

Node.js
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Java plugins

Java

Triggers

yes

User configurable commands triggered on index changes

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

optimistic locking

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

simple authentication-based access control

Users and roles with access to stored procedures

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