DBMS > Altibase vs. Google BigQuery vs. HEAVY.AI

System Properties Comparison Altibase vs. Google BigQuery vs. HEAVY.AI

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Relational 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

altibase.com

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

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

cloud.google.com/bigquery/docs

docs.heavy.ai

Developer

Altibase

Google

HEAVY.AI, Inc.

Initial release

1999

2010

2016

Current release

v7.3, 2023, August 2023

5.10, January 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Apache Version 2; enterprise edition available

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++

C++ and CUDA

Server operating systems

AIX
HP-UX
Linux

hosted

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

Supported programming languages

C
C++
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

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

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