DBMS > Google BigQuery vs. Microsoft Azure SQL Database vs. Oracle vs. Sqrrl vs. Teradata

System Properties Comparison Google BigQuery vs. Microsoft Azure SQL Database vs. Oracle vs. Sqrrl vs. Teradata

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Large scale data warehouse service with append-only tables

Database as a Service offering with high compatibility to Microsoft SQL Server

Widely used RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

cloud.google.com/bigquery

azure.microsoft.com/en-us/products/azure-sql/database

www.oracle.com/database

sqrrl.com

www.teradata.com

Technical documentation

cloud.google.com/bigquery/docs

docs.microsoft.com/en-us/azure/azure-sql

docs.oracle.com/en/database

docs.teradata.com

Developer

Google

Microsoft

Oracle

Amazon

originally Sqrrl Data, Inc.

Teradata

Initial release

2010

1980

2012

1984

Current release

V12

23c, September 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

restricted free version is 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++

C and C++

Java

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

hosted
Linux

Data scheme

yes

Schemaless in JSON and XML columns

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL

PL/SQL

also stored procedures in Java possible

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

making use of Hadoop

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

selectable replication factor

making use of Hadoop

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

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

isolation level can be parameterized

Atomic updates per row, document, or graph entity

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

Version 12c introduced the new option 'Oracle Database In-Memory'

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

fine grained access rights according to SQL-standard

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