DBMS > Apache Hive vs. DuckDB vs. ObjectBox

System Properties Comparison Apache Hive vs. DuckDB vs. ObjectBox

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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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Time Series DBMS

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

Score	75.77
Rank	#16	Overall
	#11	Relational DBMS

Score	7.44
Rank	#44	Overall
	#27	Relational DBMS

Score	1.11
Rank	#175	Overall
	#7	Object oriented DBMS
	#13	Vector DBMS

Website

hive.apache.org

duckdb.org

github.com/objectbox
objectbox.io

Technical documentation

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

duckdb.org/docs

docs.objectbox.io

Developer

Apache Software Foundation

initially developed by Facebook

ObjectBox Limited

Initial release

2012

2018

2017

Current release

3.1.3, April 2022

1.0.0, June 2024

4.0 (May 2024)

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Bindings are released under Apache 2.0

Apache License 2.0

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++

C and C++

Server operating systems

All OS with a Java VM

server-less

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Proprietary native API

Supported programming languages

C++
Java
PHP
Python

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Data sync between devices allowing occasional connected databases to work completely offline

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

yes, multi-version concurrency control (MVCC)

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

yes

More information provided by the system vendor

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