DBMS > Google Cloud Spanner vs. Microsoft SQL Server vs. SAP HANA vs. SWC-DB vs. Trafodion

System Properties Comparison Google Cloud Spanner vs. Microsoft SQL Server vs. SAP HANA vs. SWC-DB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Microsofts flagship relational DBMS

In-memory, column based data store. Available as appliance or cloud service

A high performance, scalable Wide Column DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Time Series DBMS

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

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

cloud.google.com/spanner

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

www.sap.com/products/hana.html

github.com/kashirin-alex/swc-db
www.swcdb.org

trafodion.apache.org

Technical documentation

cloud.google.com/spanner/docs

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

help.sap.com/hana

trafodion.apache.org/documentation.html

Developer

Google

Microsoft

SAP

Alex Kashirin

Apache Software Foundation, originally developed by HP

Initial release

2017

1989

2010

2020

2014

Current release

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

0.5, April 2021

2.3.0, February 2019

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

GPL V3

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java

Server operating systems

hosted

Linux
Windows

Appliance or cloud-service

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

SQL-like query language

yes

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

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

JDBC
ODBC

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

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

C++

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

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

SQLScript, R

Java Stored Procedures

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

yes, but depending on the SQL-Server Edition

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

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

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

yes

fine grained access rights according to SQL-standard

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