DBMS > Apache Cassandra vs. Badger vs. IBM Db2 Event Store vs. KairosDB

System Properties Comparison Apache Cassandra vs. Badger vs. IBM Db2 Event Store vs. KairosDB

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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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Distributed Event Store optimized for Internet of Things use cases

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Wide column store

Key-value store

Event Store
Time Series DBMS

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Website

cassandra.apache.org

github.com/dgraph-io/badger

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

github.com/kairosdb/kairosdb

Technical documentation

cassandra.apache.org/doc/latest

godoc.org/github.com/dgraph-io/badger

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

kairosdb.github.io

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

DGraph Labs

IBM

Initial release

2008

2017

2013

Current release

5.0-rc1, July 2024

2.0

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

Apache 2.0

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++

Java

Server operating systems

BSD
Linux
OS X
Windows

BSD
Linux
OS X
Solaris
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

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

yes

through the embedded Spark runtime

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

Graphite protocol
HTTP REST
Telnet API

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

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

none

Active-active shard replication

selectable replication factor

based on Cassandra

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

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

simple password-based access control

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

Apache 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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