DBMS > Hive vs. Postgres-XL vs. TerarkDB vs. TerminusDB

System Properties Comparison Hive vs. Postgres-XL vs. TerarkDB vs. TerminusDB

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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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

hive.apache.org

www.postgres-xl.org

github.com/bytedance/terarkdb

terminusdb.com

Technical documentation

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

www.postgres-xl.org/documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

initially developed by Facebook

ByteDance, originally Terark

DataChemist Ltd.

Initial release

2012

2014

since 2012, originally named StormDB

2016

2018

Current release

3.1.3, April 2022

10 R1, October 2018

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Mozilla public license

commercial

restricted open source version available

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

All OS with a Java VM

Linux
macOS

Linux

Data scheme

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
Thrift

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

C++ API
Java API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
Java
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Journaling Streams

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

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

fine grained access rights according to SQL-standard

Role-based access control

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More resources

DB-Engines blog posts

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