DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. GridDB vs. InfluxDB

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. GridDB vs. InfluxDB

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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

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

Scalable in-memory time series database optimized for IoT and Big Data

DBMS for storing time series, events and metrics

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS

with GEO package

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Website

aws.amazon.com/redshift

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

griddb.net

www.influxdata.com/products/influxdb-overview

Technical documentation

docs.aws.amazon.com/redshift

docs.griddb.net

docs.influxdata.com/influxdb

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

Toshiba Corporation

Initial release

2012

2016

2013

Current release

1703

5.1, August 2022

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

MIT-License; commercial enterprise version available

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

C++

Server operating systems

hosted

Linux

Linux
OS X

through Homebrew

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

numerical, string, blob, geometry, boolean, timestamp

Numeric data and Strings

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

APIs and other access methods

JDBC
ODBC

LDAP

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API
JSON over UDP

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

in enterprise version only

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

in enterprise version only

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID at container level

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

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

LDAP bind authentication

Access rights for users can be defined per database

simple rights management via user accounts

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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