DBMS > Altibase vs. Apache Doris vs. Google BigQuery vs. Linter vs. VoltDB

System Properties Comparison Altibase vs. Apache Doris vs. Google BigQuery vs. Linter vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

An MPP-based analytics DBMS embracing the MySQL protocol

Large scale data warehouse service with append-only tables

RDBMS for high security requirements

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

altibase.com

doris.apache.org
github.com/apache/doris

cloud.google.com/bigquery

linter.ru

www.voltdb.com

Technical documentation

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

github.com/apache/doris/wiki

cloud.google.com/bigquery/docs

docs.voltdb.com

Developer

Altibase

Apache Software Foundation, originally contributed from Baidu

Google

relex.ru

VoltDB Inc.

Initial release

1999

2017

2010

1990

2010

Current release

v7.3, 2023, August 2023

1.2.2, February 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C and C++

Java, C++

Server operating systems

AIX
HP-UX
Linux

Linux

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
OS X

for development

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

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
MySQL client

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C++
Java

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

Multi-source replication
Source-replica 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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

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