DBMS > Altibase vs. Amazon Redshift vs. GridGain vs. Hive vs. JaguarDB

System Properties Comparison Altibase vs. Amazon Redshift vs. GridGain vs. Hive vs. JaguarDB

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Large scale data warehouse service for use with business intelligence tools

GridGain is an in-memory computing platform, built on Apache Ignite

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Key-value store
Vector DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Website

altibase.com

aws.amazon.com/redshift

www.gridgain.com

hive.apache.org

www.jaguardb.com

Technical documentation

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

docs.aws.amazon.com/redshift

www.gridgain.com/docs/index.html

cwiki.apache.org/confluence/display/Hive/Home

www.jaguardb.com/support.html

Developer

Altibase

Amazon (based on PostgreSQL)

GridGain Systems, Inc.

Apache Software Foundation

initially developed by Facebook

DataJaguar, Inc.

Initial release

1999

2012

2007

2012

2015

Current release

v7.3, 2023, August 2023

GridGain 8.5.1

3.1.3, April 2022

3.3 July 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Apache Version 2

Open Source

GPL V3.0

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++, .Net

Java

C++

the server part. Clients available in other languages

Server operating systems

AIX
HP-UX
Linux

hosted

Linux
OS X
Solaris
Windows

All OS with a Java VM

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.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

ANSI SQL-92

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
Thrift

JDBC
ODBC

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
PHP
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in Python

yes (compute grid and cache interceptors can be used instead)

yes

user defined functions and integration of map-reduce

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

selectable replication factor

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

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

Security Hooks for custom implementations

Access rights for users, groups and roles

rights management via user accounts

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