DBMS > Google BigQuery vs. Sadas Engine vs. Sequoiadb vs. TerminusDB

System Properties Comparison Google BigQuery vs. Sadas Engine vs. Sequoiadb vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

NewSQL database with distributed OLTP and SQL

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Document store
Relational DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

cloud.google.com/bigquery

www.sadasengine.com

www.sequoiadb.com

terminusdb.com

Technical documentation

cloud.google.com/bigquery/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

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

terminusdb.github.io/terminusdb/#

Developer

Google

SADAS s.r.l.

Sequoiadb Ltd.

DataChemist Ltd.

Initial release

2010

2006

2013

2018

Current release

8.0

11.0.0, January 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Server: AGPL; Client: Apache V2

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

hosted

AIX
Linux
Windows

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

proprietary protocol using JSON

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
C++
Java
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

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

simple password-based access control

Role-based access control

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