DBMS > Amazon Redshift vs. Apache Druid vs. Atos Standard Common Repository vs. H2GIS vs. Prometheus

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Atos Standard Common Repository vs. H2GIS vs. Prometheus

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Spatial extension of H2

Open-source Time Series DBMS and monitoring system

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Document store
Key-value store

Spatial DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Website

aws.amazon.com/redshift

druid.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.h2gis.org

prometheus.io

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

www.h2gis.org/docs/home

prometheus.io/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

Atos Convergence Creators

CNRS

Initial release

2012

2016

2013

2015

Current release

29.0.1, April 2024

1703

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Open Source

LGPL 3.0

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

Java

Server operating systems

hosted

Linux
OS X
Unix

Linux

Linux
Windows

Data scheme

yes

schema-less columns are supported

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL for querying

yes

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

LDAP

RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages with LDAP bindings

Java

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

cell division

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

yes

based on H2

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

Immediate Consistency

none

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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

User concepts

Access control

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

LDAP bind authentication

yes

based on H2

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