DBMS > Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. MySQL vs. SAP SQL Anywhere

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. MySQL vs. SAP SQL Anywhere

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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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Widely used open source 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

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

cloud.google.com/bigtable

azure.microsoft.com/services/synapse-analytics

www.mysql.com

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

Technical documentation

cloud.google.com/bigtable/docs

docs.microsoft.com/azure/synapse-analytics

dev.mysql.com/doc

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

SAP

formerly Sybase

Initial release

2015

2016

1995

1992

Current release

8.4.0, April 2024

17, July 2015

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

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.

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Implementation language

C++

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

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
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

C#
Java
PHP

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

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

Server-side scripts

Stored procedures

Transact SQL

yes

proprietary syntax

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-row operations

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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)

yes

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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