DBMS > Altibase vs. Apache Phoenix vs. EXASOL vs. Google BigQuery

System Properties Comparison Altibase vs. Apache Phoenix vs. EXASOL vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A scale-out RDBMS with evolutionary schema built on Apache HBase

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Large scale data warehouse service with append-only tables

Primary database model

Relational DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

altibase.com

phoenix.apache.org

www.exasol.com

cloud.google.com/bigquery

Technical documentation

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

phoenix.apache.org

www.exasol.com/resources

cloud.google.com/bigquery/docs

Developer

Altibase

Apache Software Foundation

Exasol

Google

Initial release

1999

2014

2000

2010

Current release

v7.3, 2023, August 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

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

Server operating systems

AIX
HP-UX
Linux

Linux
Unix
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

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

JDBC

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

Supported programming languages

C
C++
Java

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual 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

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users, groups and roles according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

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