DBMS > Amazon Redshift vs. Google Cloud Bigtable vs. Interbase vs. SpatiaLite

System Properties Comparison Amazon Redshift vs. Google Cloud Bigtable vs. Interbase vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Light-weight proven RDBMS

originally from Borland

Spatial extension of SQLite

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

aws.amazon.com/redshift

cloud.google.com/bigtable

www.embarcadero.com/products/interbase

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.aws.amazon.com/redshift

cloud.google.com/bigtable/docs

docs.embarcadero.com/products/interbase

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Amazon (based on PostgreSQL)

Google

Embarcadero

Alessandro Furieri

Initial release

2012

2015

1984

2008

Current release

InterBase 2020, December 2019

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

server-less

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

export as XML data possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Interbase procedure and trigger language

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

Interbase Change Views

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

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 single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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