DBMS > Altibase vs. Axibase vs. Blazegraph vs. Firebird vs. Google Cloud Datastore

System Properties Comparison Altibase vs. Axibase vs. Blazegraph vs. Firebird vs. Google Cloud Datastore

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

An enterprise grade, high-performance RDBMS

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Firebird is an open source RDBMS forked from Borland's InterBase

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Primary database model

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Website

altibase.com

axibase.com/docs/atsd/finance

blazegraph.com

www.firebirdsql.org

cloud.google.com/datastore

Technical documentation

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

wiki.blazegraph.com

www.firebirdsql.org/en/reference-manuals

cloud.google.com/datastore/docs

Developer

Altibase

Axibase Corporation

Blazegraph

Firebird Foundation

Google

Initial release

1999

2013

2006

2000

As fork of Borland's InterBase

2008

Current release

v7.3, 2023, August 2023

15585

2.1.5, March 2019

5.0.0, January 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

extended commercial license available

Open Source

Initial Developer's Public License

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

C++

Java

C and C++

Server operating systems

AIX
HP-UX
Linux

Linux

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

RDF literal types

yes

yes, details here

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

ANSI SQL-92

SQL-like query language

SPARQL is used as query language

yes

SQL-like query language (GQL)

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Supported programming languages

C
C++
Java

Go
Java
PHP
Python
R
Ruby

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

PSQL

using Google App Engine

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Source-replica replication

Multi-source replication using Paxos

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 or Eventual Consistency depending on configuration

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Users with fine-grained authorization concept

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

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