DBMS > Google Cloud Bigtable vs. Interbase vs. Microsoft SQL Server vs. SAP Adaptive Server vs. SAP SQL Anywhere

System Properties Comparison Google Cloud Bigtable vs. Interbase vs. Microsoft SQL Server vs. SAP Adaptive Server vs. SAP SQL Anywhere

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.

Light-weight proven RDBMS

originally from Borland

Microsofts flagship relational DBMS

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

cloud.google.com/bigtable

www.embarcadero.com/products/interbase

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

www.sap.com/products/technology-platform/sybase-ase.html

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

cloud.google.com/bigtable/docs

docs.embarcadero.com/products/interbase

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

help.sap.com/docs/SAP_ASE

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

Embarcadero

Microsoft

SAP, Sybase

SAP

formerly Sybase

Initial release

2015

1984

1989

1987

1992

Current release

InterBase 2020, December 2019

SQL Server 2022, November 2022

16.0

17, July 2015

License

Commercial or Open Source

commercial

restricted free version is available

commercial

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++

C and C++

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

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)

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

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

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

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

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

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

Java and Transact-SQL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Interbase Change Views

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

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

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

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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