DBMS > Google Cloud Bigtable vs. MonetDB vs. PieCloudDB vs. Snowflake vs. UniData,UniVerse

System Properties Comparison Google Cloud Bigtable vs. MonetDB vs. PieCloudDB vs. Snowflake vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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 relational database management system that stores data in columns

A cloud-native analytic database platform with new technologoy for elastic MPP

Cloud-based data warehousing service for structured and semi-structured data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store
Wide column store

Relational DBMS

Multivalue DBMS

Secondary database models

Document store
Spatial DBMS

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

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.25
Rank	#304	Overall
	#138	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

cloud.google.com/bigtable

www.monetdb.org

www.openpie.com

www.snowflake.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

cloud.google.com/bigtable/docs

www.monetdb.org/Documentation

docs.snowflake.net/manuals/index.html

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Google

MonetDB BV

OpenPie

Snowflake Computing Inc.

Rocket Software

Initial release

2015

2004

2014

1985

Current release

Dec2023 (11.49), December 2023

2.1, January 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

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

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

APIs and other access methods

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

CLI Client
JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

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

Java
PL/SQL
Python
R

JavaScript (Node.js)
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes, in SQL, C, R

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Source-replica replication available in experimental status

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-row operations

ACID

configurable

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

fine grained access rights according to SQL-standard

User Roles and pluggable authentication with full SQL Standard

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Licensing and pricing models

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