DBMS > Google Cloud Spanner vs. IBM Db2 vs. SAP HANA vs. SiteWhere vs. YDB

System Properties Comparison Google Cloud Spanner vs. IBM Db2 vs. SAP HANA vs. SiteWhere vs. YDB

Editorial information provided by DB-Engines

Name

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.

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

M2M integration platform for persisting/querying time series data

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

cloud.google.com/spanner

www.ibm.com/products/db2

www.sap.com/products/hana.html

github.com/sitewhere/sitewhere

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

cloud.google.com/spanner/docs

www.ibm.com/docs/en/db2

help.sap.com/hana

sitewhere1.sitewhere.io/index.html

ydb.tech/en/docs

Developer

Google

IBM

SAP

SiteWhere

Yandex

Initial release

2017

1983

host version

2010

2019

Current release

12.1, October 2016

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free version is available

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache 2.0; commercial license available

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Appliance or cloud-service

Linux
OS X
Windows

Linux

Data scheme

yes

predefined scheme

Flexible Schema (defined schema, partial schema, schema free)

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

SQL-like query language (YQL)

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
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

HTTP REST

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

yes

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

yes

with separate tools (MQ, InfoSphere)

yes

selectable replication factor

based on HBase

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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

Users with fine-grained authorization concept

Access rights defined for Yandex Cloud users

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