DBMS > Hazelcast vs. Hive vs. SQLite vs. STSdb

System Properties Comparison Hazelcast vs. Hive vs. SQLite vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

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

Widely used embeddable, in-process RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store

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	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

hazelcast.com

hive.apache.org

www.sqlite.org

github.com/STSSoft/STSdb4

Technical documentation

hazelcast.org/imdg/docs

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

www.sqlite.org/docs.html

Developer

Hazelcast

Apache Software Foundation

initially developed by Facebook

Dwayne Richard Hipp

STS Soft SC

Initial release

2008

2012

2000

2011

Current release

5.3.6, November 2023

3.1.3, April 2022

3.46.0 (23 May 2024), May 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2

Open Source

Public Domain

Open Source

GPLv2, commercial license 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

server-less

Windows

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

primitive types and user defined types (classes)

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 query language

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
Thrift

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.NET Client API

Supported programming languages

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

C++
Java
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C#
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

user defined functions and integration of map-reduce

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Role-based access control

Access rights for users, groups and roles

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