DBMS > Cassandra vs. InfinityDB vs. SAP Adaptive Server vs. SWC-DB

System Properties Comparison Cassandra vs. InfinityDB vs. SAP Adaptive Server vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A Java embedded Key-Value Store which extends the Java Map interface

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

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

with Boeing's Spatial Query Server

Time Series DBMS

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

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

cassandra.apache.org

boilerbay.com

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

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

Technical documentation

cassandra.apache.org/doc/latest

boilerbay.com/infinitydb/manual

help.sap.com/docs/SAP_ASE

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Boiler Bay Inc.

SAP, Sybase

Alex Kashirin

Initial release

2008

2002

1987

2020

Current release

4.1.3, July 2023

4.0

16.0

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

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++

C++

Server operating systems

BSD
Linux
OS X
Windows

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

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

yes

SQL-like query language

APIs and other access methods

Proprietary protocol

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

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

Proprietary protocol
Thrift

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java

C
C++
Cobol
Java
Java
Perl
PHP
Python

C++

Server-side scripts

Stored procedures

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

none

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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Optimistic locking for transactions; no isolation for bulk loads

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.

User concepts

Access control

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

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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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.
» more

Licensing and pricing models

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