DBMS > Altibase vs. Google BigQuery vs. Interbase vs. Microsoft Azure Cosmos DB vs. Yanza

System Properties Comparison Altibase vs. Google BigQuery vs. Interbase vs. Microsoft Azure Cosmos DB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

An enterprise grade, high-performance RDBMS

Large scale data warehouse service with append-only tables

Light-weight proven RDBMS

originally from Borland

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

altibase.com

cloud.google.com/bigquery

www.embarcadero.com/products/interbase

azure.microsoft.com/services/cosmos-db

yanza.com

Technical documentation

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

cloud.google.com/bigquery/docs

docs.embarcadero.com/products/interbase

learn.microsoft.com/azure/cosmos-db

Developer

Altibase

Google

Embarcadero

Microsoft

Yanza

Initial release

1999

2010

1984

2014

2015

Current release

v7.3, 2023, August 2023

InterBase 2020, December 2019

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

AIX
HP-UX
Linux

hosted

Android
iOS
Linux
OS X
Windows

hosted

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

export as XML data possible

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

ANSI SQL-92

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API

Supported programming languages

C
C++
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in JavaScript

yes

Interbase procedure and trigger language

JavaScript

Triggers

yes

JavaScript

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Interbase Change Views

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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