DBMS > Badger vs. Cassandra vs. Datomic vs. Kdb

System Properties Comparison Badger vs. Cassandra vs. Datomic vs. Kdb

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Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

High performance Time Series DBMS

Primary database model

Key-value store

Wide column store

Relational DBMS

Time Series DBMS
Vector DBMS

Secondary database models

Vector DBMS

starting with release V5

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Website

github.com/dgraph-io/badger

cassandra.apache.org

www.datomic.com

kx.com

Technical documentation

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

cassandra.apache.org/doc/latest

docs.datomic.com

code.kx.com

Developer

DGraph Labs

Apache Software Foundation

Apache top level project, originally developped by Facebook

Cognitect

Kx Systems, a division of First Derivatives plc

Initial release

2017

2008

2012

2000

kdb was released 2000, kdb+ in 2003

Current release

4.1.3, July 2023

1.0.6735, June 2023

3.6, May 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

limited edition free

commercial

free 32-bit version

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

Java, Clojure

Server operating systems

BSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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.

yes

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

table attribute 'grouped'

SQL

Support of SQL

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

SQL-like query language (q)

APIs and other access methods

Proprietary protocol

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

RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Clojure
Java

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

Triggers

yes

By using transaction functions

yes

with views

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

none

But extensive use of caching in the application peers

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

none

But extensive use of caching in the application peers

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users can be defined per object

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
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kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

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