DBMS > Amazon Redshift vs. InterSystems Caché vs. Kinetica vs. PlanetScale vs. Prometheus

System Properties Comparison Amazon Redshift vs. InterSystems Caché vs. Kinetica vs. PlanetScale vs. Prometheus

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A multi-model DBMS and application server

Fully vectorized database across both GPUs and CPUs

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Open-source Time Series DBMS and monitoring system

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Website

aws.amazon.com/redshift

www.intersystems.com/products/cache

www.kinetica.com

planetscale.com

prometheus.io

Technical documentation

docs.aws.amazon.com/redshift

docs.intersystems.com

docs.kinetica.com

planetscale.com/docs

prometheus.io/docs

Developer

Amazon (based on PostgreSQL)

InterSystems

Kinetica

PlanetScale

Initial release

2012

1997

2012

2020

2015

Current release

2018.1.4, May 2020

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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.

Implementation language

C, C++

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

Docker
Linux
macOS

Linux
Windows

Data scheme

yes

depending on used data model

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Java

C++
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions

yes

proprietary syntax

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency across shards
Immediate Consistency within a shard

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

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