DBMS > Google BigQuery vs. Graph Engine vs. MySQL vs. SAP Adaptive Server

System Properties Comparison Google BigQuery vs. Graph Engine vs. MySQL vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Widely used open source RDBMS

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

cloud.google.com/bigquery

www.graphengine.io

www.mysql.com

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

dev.mysql.com/doc

help.sap.com/docs/SAP_ASE

Developer

Google

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

SAP, Sybase

Initial release

2010

1995

1987

Current release

8.4.0, April 2024

16.0

License

Commercial or Open Source

commercial

Open Source

MIT License

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

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Implementation language

.NET and C

C and C++

Server operating systems

hosted

.NET

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

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

RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

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

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Since BigQuery is designed for querying data

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent 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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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