DBMS > Hive vs. HyperSQL vs. OpenMLDB vs. Realm

System Properties Comparison Hive vs. HyperSQL vs. OpenMLDB vs. Realm

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

An open-source machine learning database that provides a feature platform for training and inference

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Relational DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

openmldb.ai/docs/zh/main

realm.io/docs

Developer

Apache Software Foundation

initially developed by Facebook

4 Paradigm Inc.

Realm, acquired by MongoDB in May 2019

Initial release

2012

2001

2020

2014

Current release

3.1.3, April 2022

2.7.2, June 2023

2024-2 February 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

based on BSD license

Open Source

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++, Java, Scala

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

Android
Backend: server-less
iOS
Windows

Data scheme

yes

Fixed schema

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Thrift

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
SQLAlchemy

Supported programming languages

C++
Java
PHP
Python

All languages supporting JDBC/ODBC
Java

C++
Go
Java
Python
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java, SQL

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes

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More resources

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