DBMS > Google Cloud Spanner vs. IBM Db2 Event Store vs. MySQL vs. SAP HANA vs. UniData,UniVerse

System Properties Comparison Google Cloud Spanner vs. IBM Db2 Event Store vs. MySQL vs. SAP HANA vs. UniData,UniVerse

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.

Distributed Event Store optimized for Internet of Things use cases

Widely used open source RDBMS

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Multivalue DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

cloud.google.com/spanner

www.ibm.com/products/db2-event-store

www.mysql.com

www.sap.com/products/hana.html

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

cloud.google.com/spanner/docs

www.ibm.com/docs/en/db2-event-store

dev.mysql.com/doc

help.sap.com/hana

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Google

IBM

Oracle

since 2010, originally MySQL AB, then Sun

SAP

Rocket Software

Initial release

2017

1995

2010

1985

Current release

2.0

8.4.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

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.

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Implementation language

C and C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

through the embedded Spark runtime

yes

with proprietary extensions

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
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

proprietary syntax

SQLScript, R

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

Active-active shard replication

Multi-source replication
Source-replica replication

yes

Source-replica 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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

not for MyISAM storage engine

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Users with fine-grained authorization concept

no user groups or roles

yes

Access rights according to SQL-standard and operating system based

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