DBMS > Cassandra vs. Hazelcast vs. Hyprcubd vs. Ingres vs. Kinetica

System Properties Comparison Cassandra vs. Hazelcast vs. Hyprcubd vs. Ingres vs. Kinetica

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A widely adopted in-memory data grid

Serverless Time Series DBMS

Well established RDBMS

Fully vectorized database across both GPUs and CPUs

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Document store

JSON support with IMDG 3.12

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	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Website

cassandra.apache.org

hazelcast.com

hyprcubd.com (offline)

www.actian.com/databases/ingres

www.kinetica.com

Technical documentation

cassandra.apache.org/doc/latest

hazelcast.org/imdg/docs

docs.actian.com/ingres

docs.kinetica.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Hazelcast

Hyprcubd, Inc.

Actian Corporation

Kinetica

Initial release

2008

1974

originally developed at University Berkely in early 1970s

2012

Current release

4.1.3, July 2023

5.3.6, November 2023

11.2, May 2022

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

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

All OS with a Java VM

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

the object must implement a serialization strategy

but tools for importing/exporting data from/to XML-files available

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)

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

Proprietary protocol

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

JCache
JPA
Memcached protocol
RESTful HTTP API

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

user defined functions

Triggers

yes

Events

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"

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

Replicated Map

Ingres Replicator

Source-replica replication

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users can be defined per object

Role-based access control

token access

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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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