DBMS > Amazon Redshift vs. Hyprcubd vs. Kinetica vs. Memcached

System Properties Comparison Amazon Redshift vs. Hyprcubd vs. Kinetica vs. Memcached

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Editorial information provided by DB-Engines

Name

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

Description

Large scale data warehouse service for use with business intelligence tools

Serverless Time Series DBMS

Fully vectorized database across both GPUs and CPUs

In-memory key-value store, originally intended for caching

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	16.84
Rank	#32	Overall
	#4	Key-value stores

Website

aws.amazon.com/redshift

hyprcubd.com (offline)

www.kinetica.com

www.memcached.org

Technical documentation

docs.aws.amazon.com/redshift

docs.kinetica.com

github.com/memcached/memcached/wiki

Developer

Amazon (based on PostgreSQL)

Hyprcubd, Inc.

Kinetica

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Initial release

2012

2003

Current release

7.1, August 2021

1.6.29, June 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

gRPC (https)

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

token access

Access rights for users and roles on table level

yes

using SASL (Simple Authentication and Security Layer) protocol

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