DBMS > Apache Cassandra vs. Kdb vs. Postgres-XL vs. TimescaleDB

System Properties Comparison Apache Cassandra vs. Kdb vs. Postgres-XL vs. TimescaleDB

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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

High performance Time Series DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Wide column store

Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

Relational DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

Technical documentation

cassandra.apache.org/doc/latest

code.kx.com

www.postgres-xl.org/documentation

docs.timescale.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Kx Systems, a division of First Derivatives plc

Timescale

Initial release

2008

2000

kdb was released 2000, kdb+ in 2003

2014

since 2012, originally named StormDB

2017

Current release

5.0-rc1, July 2024

3.6, May 2018

10 R1, October 2018

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free 32-bit version

Open Source

Mozilla public license

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

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

XML type, but no XML query functionality

yes

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

table attribute 'grouped'

yes

SQL

Support of SQL

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

SQL-like query language (q)

yes

distributed, parallel query execution

yes

full PostgreSQL SQL syntax

APIs and other access methods

Proprietary protocol

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

Source-replica replication with hot standby and reads on replicas

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

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

MVCC

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

Access rights for users can be defined per object

rights management via user accounts

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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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...
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Market metrics

Apache 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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