DBMS > Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. OpenEdge vs. RDF4J

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. OpenEdge vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering with high compatibility to Microsoft SQL Server

Microsofts flagship relational DBMS

Application development environment with integrated database management system

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Key-value store
Wide column store

Relational DBMS

RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

cloud.google.com/bigtable

azure.microsoft.com/en-us/products/azure-sql/database

www.microsoft.com/en-us/sql-server

www.progress.com/openedge

rdf4j.org

Technical documentation

cloud.google.com/bigtable/docs

docs.microsoft.com/en-us/azure/azure-sql

learn.microsoft.com/en-US/sql/sql-server

documentation.progress.com/output/ua/OpenEdge_latest

rdf4j.org/documentation

Developer

Google

Microsoft

Progress Software Corporation

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2015

2010

1989

1984

2004

Current release

V12

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

APIs and other access methods

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Progress proprietary ABL (Advanced Business Language)

Java
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, with always 3 replicas available

yes, but depending on the SQL-Server Edition

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Users and groups

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