DBMS > Apache Hive vs. Machbase Neo vs. PostgreSQL

System Properties Comparison Apache Hive vs. Machbase Neo vs. PostgreSQL

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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

TimeSeries DBMS for AIoT and BigData

Widely used open source RDBMS

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

Primary database model

Relational DBMS

Time Series DBMS

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 Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	72.65
Rank	#18	Overall
	#12	Relational DBMS

Score	0.08
Rank	#344	Overall
	#31	Time Series DBMS

Score	667.25
Rank	#4	Overall
	#4	Relational DBMS

Website

hive.apache.org

machbase.com

www.postgresql.org

Technical documentation

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

machbase.com/dbms

www.postgresql.org/docs

Developer

Apache Software Foundation

initially developed by Facebook

Machbase

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2012

2013

1989

1989: Postgres, 1996: PostgreSQL

Current release

3.1.3, April 2022

V8.0, August 2023

16.4, August 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free test version available

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

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

Data scheme

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

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC
Thrift

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

Supported programming languages

C++
Java
PHP
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.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

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

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

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

volatile and lookup table

User concepts

Access control

Access rights for users, groups and roles

simple password-based access control

fine grained access rights according to SQL-standard

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