DBMS > GridGain vs. Hive vs. Oracle Rdb vs. SwayDB

System Properties Comparison GridGain vs. Hive vs. Oracle Rdb vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

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

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Key-value store

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

Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Website

www.gridgain.com

hive.apache.org

www.oracle.com/database/technologies/related/rdb.html

swaydb.simer.au

Technical documentation

www.gridgain.com/docs/index.html

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

GridGain Systems, Inc.

Apache Software Foundation

initially developed by Facebook

Oracle, originally developed by Digital Equipment Corporation (DEC)

Simer Plaha

Initial release

2007

2012

1984

2018

Current release

GridGain 8.5.1

3.1.3, April 2022

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net

Java

Scala

Server operating systems

Linux
OS X
Solaris
Windows

All OS with a Java VM

HP Open VMS

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like DML and DDL statements

yes

APIs and other access methods

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

JDBC
ODBC
Thrift

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

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

yes

user defined functions and integration of map-reduce

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

Atomic execution of operations

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

Security Hooks for custom implementations

Access rights for users, groups and roles

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More resources

DB-Engines blog posts

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