DBMS > AgensGraph vs. Google Cloud Bigtable vs. MonetDB vs. PieCloudDB vs. SAP HANA

System Properties Comparison AgensGraph vs. Google Cloud Bigtable vs. MonetDB vs. PieCloudDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Graph DBMS
Relational DBMS

Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

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	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

bitnine.net/agensgraph

cloud.google.com/bigtable

www.monetdb.org

www.openpie.com

www.sap.com/products/hana.html

Technical documentation

bitnine.net/documentation

cloud.google.com/bigtable/docs

www.monetdb.org/Documentation

help.sap.com/hana

Developer

Bitnine Global Inc.

Google

MonetDB BV

OpenPie

SAP

Initial release

2016

2015

2004

2010

Current release

2.1, December 2018

Dec2023 (11.49), December 2023

2.1, January 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Mozilla Public License 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Appliance or cloud-service

Data scheme

depending on used data model

schema-free

yes

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

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

APIs and other access methods

Cypher Query Language
JDBC

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

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

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

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

Java
PL/SQL
Python
R

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

none

Source-replica replication available in experimental status

yes

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

yes

Transaction concepts

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

ACID

Atomic single-row operations

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Key customers

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Licensing and pricing models

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