DBMS > Google BigQuery vs. Google Cloud Bigtable vs. SWC-DB

System Properties Comparison Google BigQuery vs. Google Cloud Bigtable vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store
Wide column store

Wide column store

Secondary database models

Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cloud.google.com/bigquery

cloud.google.com/bigtable

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cloud.google.com/bigquery/docs

cloud.google.com/bigtable/docs

Developer

Google

Alex Kashirin

Initial release

2010

2015

2020

Current release

0.5, April 2021

License

Commercial or Open Source

commercial

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++

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

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.

Secondary indexes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Proprietary protocol
Thrift

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C++

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

Atomic single-row operations

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)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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