DBMS > Altibase vs. Faircom EDGE vs. Google Cloud Spanner vs. Stardog

System Properties Comparison Altibase vs. Faircom EDGE vs. Google Cloud Spanner vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS
RDF store

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

altibase.com

www.faircom.com/products/faircom-edge

cloud.google.com/spanner

www.stardog.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

cloud.google.com/spanner/docs

docs.stardog.com

Developer

Altibase

FairCom Corporation

Google

Stardog-Union

Initial release

1999

1979

2017

2010

Current release

v7.3, 2023, August 2023

V3, October 2020

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Restricted, free version available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

ANSI C, C++

Java

Server operating systems

AIX
HP-UX
Linux

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Linux
macOS
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

ANSI SQL-92

yes

ANSI SQL queries

yes

Query statements complying to ANSI 2011

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
Proprietary protocol

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C
C++
Java

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Go
Java
JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

.Net, JavaScript, C/C++

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication with 3 replicas for regional instances.

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

when using SQL

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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

Access rights for users and roles

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