DBMS > Google BigQuery vs. IBM Db2 warehouse vs. JaguarDB vs. Sequoiadb vs. Transbase

System Properties Comparison Google BigQuery vs. IBM Db2 warehouse vs. JaguarDB vs. Sequoiadb vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Cloud-based data warehousing service

Performant, highly scalable DBMS for AI and IoT applications

NewSQL database with distributed OLTP and SQL

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store
Relational 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	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

www.jaguardb.com

www.sequoiadb.com

www.transaction.de/en/products/transbase.html

Technical documentation

cloud.google.com/bigquery/docs

www.jaguardb.com/support.html

www.sequoiadb.com/en/index.php?m=Files&a=index

www.transaction.de/en/products/transbase/features.html

Developer

Google

IBM

DataJaguar, Inc.

Sequoiadb Ltd.

Transaction Software GmbH

Initial release

2010

2014

2015

2013

1987

Current release

3.3 July 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

Server: AGPL; Client: Apache V2

commercial

free development license

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++

the server part. Clients available in other languages

C++

C and C++

Server operating systems

hosted

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC

proprietary protocol using JSON

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C++
Java
PHP
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL, SQL PL

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Eventual Consistency

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

Document is locked during a transaction

yes

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

rights management via user accounts

simple password-based access control

fine grained access rights according to SQL-standard

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