DBMS > Google BigQuery vs. Quasardb vs. SAP Advantage Database Server vs. SQream DB vs. TimesTen

System Properties Comparison Google BigQuery vs. Quasardb vs. SAP Advantage Database Server vs. SQream DB vs. TimesTen

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

Distributed, high-performance timeseries database

Low-cost RDBMS with access to ISAM and FoxPro data structures

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

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

cloud.google.com/bigquery

quasar.ai

www.sap.com/products/advantage-database-server.html

sqream.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

cloud.google.com/bigquery/docs

doc.quasar.ai/master

docs.sqream.com

docs.oracle.com/database/timesten-18.1

Developer

Google

quasardb

Sybase, SAP

SQream Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2010

2009

1993

2017

1998

Current release

3.14.1, January 2024

2022.1.6, December 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

BSD
Linux
OS X
Windows

Linux
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

.Net
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Delphi
Perl
PHP

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions in Python

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

none

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with selectable replication factor

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

caching of (temporary) tables can be configured

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.