DBMS > Google BigQuery vs. IBM Db2 warehouse vs. OceanBase vs. SAP SQL Anywhere vs. VelocityDB

System Properties Comparison Google BigQuery vs. IBM Db2 warehouse vs. OceanBase vs. SAP SQL Anywhere vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Cloud-based data warehousing service

A distributed, high available RDBMS compatible with Oracle and MySQL

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Wide column store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

en.oceanbase.com

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

velocitydb.com

Technical documentation

cloud.google.com/bigquery/docs

en.oceanbase.com/docs/oceanbase-database

help.sap.com/docs/SAP_SQL_Anywhere

velocitydb.com/UserGuide

Developer

Google

IBM

OceanBase

previously Alibaba and Ant Group

SAP

formerly Sybase

VelocityDB Inc

Initial release

2010

2014

2010

1992

2011

Current release

4.3.0, April 2024

17, July 2015

7.x

License

Commercial or Open Source

commercial

Open Source

Commercial license 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.

Implementation language

C++

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Any that supports .NET

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

ADO.NET
HTTP API
JDBC
ODBC

.Net

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

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

.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL, SQL PL

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

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

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

Source-replica replication

Database mirroring

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

Transaction concepts

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

Since BigQuery is designed for querying data

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

Based on Windows Authentication

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