DBMS > Adabas vs. GigaSpaces vs. Hive vs. Riak KV

System Properties Comparison Adabas vs. GigaSpaces vs. Hive vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Distributed, fault tolerant key-value store

Primary database model

Multivalue DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Graph DBMS
Search engine

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

Score	4.78
Rank	#81	Overall
	#1	Multivalue DBMS

Score	0.97
Rank	#175	Overall
	#30	Document stores
	#6	Object oriented DBMS

Score	81.61
Rank	#17	Overall
	#11	Relational DBMS

Score	6.63
Rank	#64	Overall
	#8	Key-value stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

www.gigaspaces.com

hive.apache.org

riak.com/products/riak-kv

Technical documentation

docs.gigaspaces.com/latest/landing.html

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

Developer

Software AG

Gigaspaces Technologies

Apache Software Foundation

initially developed by Facebook

Basho Technologies

Initial release

1971

2000

2012

2009

Current release

15.5, September 2020

3.1.2, August 2019

2.1.0, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

Java

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-99 for query and DML statements

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC
Thrift

HTTP API
Native Erlang Interface

Supported programming languages

Natural

.Net
C++
Java
Python
Scala

C++
Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

JavaScript and Erlang

Triggers

yes, event driven architecture

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Role-based access control

Access rights for users, groups and roles

More information provided by the system vendor

Specific characteristics

GigaSpaces, the pioneer of In-Memory Computing , drives enterprise digital transformation...
» more

Competitive advantages

AI Driven Autonomous Operations – GigaSpaces’ unique AI driven technology simplifies...
» more

Typical application scenarios

Application Acceleration, Smart Caching, BI Acceleration on Fresh Data, Digital Integration...
» more

Key customers

Morgan Stanley, Bank of America, Goldman Sachs, PriceRunner, Cerner, Societe Generale,...
» more

Market metrics

Forrester has positioned GigaSpaces as a strong performer in The Forrester Wave™:...
» more

Licensing and pricing models

GigaSpaces offers both open source and commercial editions with annual subscriptions....
» more

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