DBMS > Google Cloud Spanner vs. MySQL vs. SingleStore vs. SQream DB vs. Transbase

System Properties Comparison Google Cloud Spanner vs. MySQL vs. SingleStore vs. SQream DB vs. Transbase

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.

Widely used open source RDBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

a GPU-based, columnar RDBMS for big data analytics workloads

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

cloud.google.com/spanner

www.mysql.com

www.singlestore.com

sqream.com

www.transaction.de/en/products/transbase.html

Technical documentation

cloud.google.com/spanner/docs

dev.mysql.com/doc

docs.singlestore.com

docs.sqream.com

www.transaction.de/en/products/transbase/features.html

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

SingleStore Inc.

SQream Technologies

Transaction Software GmbH

Initial release

2017

1995

2013

2017

1987

Current release

9.0.0, July 2024

8.5, January 2024

2022.1.6, December 2022

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

free developer edition available

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++, Go

C++, CUDA, Haskell, Java, Scala

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

64 bit version required

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

with proprietary extensions

yes

but no triggers and foreign keys

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
Proprietary native API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

.Net
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

user defined functions in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

hash partitioning

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

Multi-source replication
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

can define user-defined aggregate functions for map-reduce-style calculations

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

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

yes

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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)

Users with fine-grained authorization concept

no user groups or roles

Fine grained access control via users, groups and roles

fine grained access rights according to SQL-standard

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