DBMS > Badger vs. Hive vs. Oracle vs. PostgreSQL

System Properties Comparison Badger vs. Hive vs. Oracle vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Widely used RDBMS

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	645.05
Rank	#4	Overall
	#4	Relational DBMS

Website

github.com/dgraph-io/badger

hive.apache.org

www.oracle.com/database

www.postgresql.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

docs.oracle.com/en/database

www.postgresql.org/docs

Developer

DGraph Labs

Apache Software Foundation

initially developed by Facebook

Oracle

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2017

2012

1980

1989

1989: Postgres, 1996: PostgreSQL

Current release

3.1.3, April 2022

23c, September 2023

16.2, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C++
Java
PHP
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

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