DBMS > Apache Hive vs. Hazelcast

System Properties Comparison Apache Hive vs. Hazelcast

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Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	56.87
Rank	#18	Overall
	#12	Relational DBMS

Score	5.59
Rank	#58	Overall
	#6	Key-value stores

Website

hive.apache.org

hazelcast.com

Technical documentation

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

hazelcast.org/imdg/docs

Developer

Apache Software Foundation

initially developed by Facebook

Hazelcast

Initial release

2012

2008

Current release

3.1.3, April 2022

5.3.6, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM

Data scheme

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

C++
Java
PHP
Python

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

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

Access rights for users, groups and roles

Role-based access control

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