DBMS > Amazon Redshift vs. BigObject vs. Linter vs. SQream DB

System Properties Comparison Amazon Redshift vs. BigObject vs. Linter vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

RDBMS for high security requirements

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Spatial DBMS

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

aws.amazon.com/redshift

bigobject.io

linter.ru

sqream.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

docs.sqream.com

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

relex.ru

SQream Technologies

Initial release

2012

2015

1990

2017

Current release

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free community edition 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.

Implementation language

C and C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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 DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

.Net
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

yes

proprietary syntax with the possibility to convert from PL/SQL

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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