DBMS > Amazon Redshift vs. Axibase vs. Cassandra vs. SAP Adaptive Server

System Properties Comparison Amazon Redshift vs. Axibase vs. Cassandra vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Website

aws.amazon.com/redshift

axibase.com/docs/atsd/finance

cassandra.apache.org

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

docs.aws.amazon.com/redshift

cassandra.apache.org/doc/latest

help.sap.com/docs/SAP_ASE

Developer

Amazon (based on PostgreSQL)

Axibase Corporation

Apache Software Foundation

Apache top level project, originally developped by Facebook

SAP, Sybase

Initial release

2012

2013

2008

1987

Current release

15585

4.1.3, July 2023

16.0

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C and C++

Server operating systems

hosted

Linux

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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.

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like SELECT, DML and DDL statements (CQL)

yes

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate 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

Atomicity and isolation are supported for single operations

ACID

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

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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