DBMS > Cassandra vs. IBM Db2 Event Store vs. OpenTSDB vs. SAP HANA

System Properties Comparison Cassandra vs. IBM Db2 Event Store vs. OpenTSDB vs. SAP HANA

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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

Distributed Event Store optimized for Internet of Things use cases

Scalable Time Series DBMS based on HBase

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Wide column store

Event Store
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

cassandra.apache.org

www.ibm.com/products/db2-event-store

opentsdb.net

www.sap.com/products/hana.html

Technical documentation

cassandra.apache.org/doc/latest

www.ibm.com/docs/en/db2-event-store

opentsdb.net/docs/build/html/index.html

help.sap.com/hana

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

IBM

currently maintained by Yahoo and other contributors

SAP

Initial release

2008

2017

2011

2010

Current release

4.1.3, July 2023

2.0

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free developer edition available

Open Source

LGPL

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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++

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

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

yes

through the embedded Spark runtime

yes

APIs and other access methods

Proprietary protocol

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
Telnet API

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Active-active shard replication

selectable replication factor

based on HBase

yes

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

Eventual Consistency

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

yes

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.
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Licensing and pricing models

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