DBMS > Cassandra vs. HugeGraph vs. Kinetica vs. TimesTen

System Properties Comparison Cassandra vs. HugeGraph vs. Kinetica vs. TimesTen

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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 fast-speed and highly-scalable Graph DBMS

Fully vectorized database across both GPUs and CPUs

In-Memory RDBMS compatible to Oracle

Primary database model

Wide column store

Graph DBMS

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS
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	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

cassandra.apache.org

github.com/hugegraph
hugegraph.apache.org

www.kinetica.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

cassandra.apache.org/doc/latest

hugegraph.apache.org/docs

docs.kinetica.com

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Baidu

Kinetica

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2008

2018

2012

1998

Current release

4.1.3, July 2023

0.9

7.1, August 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

commercial

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, C++

Server operating systems

BSD
Linux
OS X
Windows

Linux
macOS
Unix

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

also supports composite index and range index

yes

SQL

Support of SQL

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

SQL-like DML and DDL statements

yes

APIs and other access methods

Proprietary protocol

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

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Groovy
Java
Python

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

user defined functions

PL/SQL

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

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 or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users can be defined per object

Users, roles and permissions

Access rights for users and roles on table level

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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News

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11 June 2024

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