DBMS > Amazon Redshift vs. Blueflood vs. SAP IQ vs. SAP SQL Anywhere vs. Solr

System Properties Comparison Amazon Redshift vs. Blueflood vs. SAP IQ vs. SAP SQL Anywhere vs. Solr

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on Cassandra

Columnar RDBMS optimized for Big Data analytics

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

column-oriented

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/redshift

blueflood.io

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.sap.com/products/technology-platform/sql-anywhere.html

solr.apache.org

Technical documentation

docs.aws.amazon.com/redshift

github.com/rax-maas/blueflood/wiki

help.sap.com/docs/SAP_IQ

help.sap.com/docs/SAP_SQL_Anywhere

solr.apache.org/resources.html

Developer

Amazon (based on PostgreSQL)

Rackspace

SAP, formerly Sybase

SAP

formerly Sybase

Apache Software Foundation

Initial release

2012

2013

1994

1992

2006

Current release

16.1 SPS04, April 2019

17, July 2015

9.5.0, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

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

Server operating systems

hosted

Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

All OS with a Java VM

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

Data scheme

yes

predefined scheme

yes

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

Typing

predefined data types such as float or date

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

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

HTTP REST

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, in C/C++, Java, .Net or Perl

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

SAP/Sybase Replication Server

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

yes

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