DBMS > Google BigQuery vs. SQream DB vs. WakandaDB

System Properties Comparison Google BigQuery vs. SQream DB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Object oriented DBMS

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Trend Chart

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

cloud.google.com/bigquery

sqream.com

wakanda.github.io

Technical documentation

cloud.google.com/bigquery/docs

docs.sqream.com

wakanda.github.io/doc

Developer

Google

SQream Technologies

Wakanda SAS

Initial release

2010

2017

2012

Current release

2022.1.6, December 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

AGPLv3, extended commercial license available

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++, CUDA, Haskell, Java, Scala

C++, JavaScript

Server operating systems

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

.Net
JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

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.

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

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