DBMS > EDB Postgres vs. FatDB vs. Google Cloud Bigtable vs. SAP HANA

System Properties Comparison EDB Postgres vs. FatDB vs. Google Cloud Bigtable vs. SAP HANA

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

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

Primary database model

Relational DBMS

Document store
Key-value store

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	1.86
Rank	#131	Overall
	#61	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

www.enterprisedb.com

cloud.google.com/bigtable

www.sap.com/products/hana.html

Technical documentation

www.enterprisedb.com/docs

cloud.google.com/bigtable/docs

help.sap.com/hana

Developer

EnterpriseDB

FatCloud

Google

SAP

Initial release

2005

2012

2015

2010

Current release

14, December 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

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
Windows

Windows

hosted

Appliance or cloud-service

Data scheme

yes

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

Via inetgration in SQL Server

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

via applications

SQLScript, R

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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, multi-version concurrency control (MVCC)

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

Can implement custom security layer via applications

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

yes

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