DBMS > AlaSQL vs. EDB Postgres vs. Google Cloud Bigtable vs. RDF4J

System Properties Comparison AlaSQL vs. EDB Postgres vs. Google Cloud Bigtable vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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.

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Wide column store

RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	1.86
Rank	#131	Overall
	#61	Relational DBMS

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

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

alasql.org

www.enterprisedb.com

cloud.google.com/bigtable

rdf4j.org

Technical documentation

github.com/AlaSQL/alasql

www.enterprisedb.com/docs

cloud.google.com/bigtable/docs

rdf4j.org/documentation

Developer

Andrey Gershun & Mathias R. Wulff

EnterpriseDB

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2014

2005

2015

2004

Current release

14, December 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

BSD for PostgreSQL-components

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

JavaScript

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
Windows

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

standard with numerous extensions

APIs and other access methods

JavaScript API

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

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

JavaScript

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

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

Java
PHP
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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

by hash, list or range

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Atomic single-row operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

in-memory storage is supported as well

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)

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