DBMS > Hive vs. OpenEdge vs. Prometheus

System Properties Comparison Hive vs. OpenEdge vs. Prometheus

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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

Application development environment with integrated database management system

Open-source TimeSeries DBMS and monitoring system

Primary database model

Relational DBMS

Time Series DBMS

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

Score	79.48
Rank	#17	Overall
	#11	Relational DBMS

Score	4.37
Rank	#86	Overall
	#45	Relational DBMS

Score	6.69
Rank	#63	Overall
	#3	Time Series DBMS

Website

hive.apache.org

www.progress.com/openedge

prometheus.io

Technical documentation

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

documentation.progress.com/output/ua/OpenEdge_latest

prometheus.io/docs

Developer

Apache Software Foundation

initially developed by Facebook

Progress Software Corporation

Initial release

2012

1984

2015

Current release

3.1.2, August 2019

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

close to SQL 92

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

C++
Java
PHP
Python

Progress proprietary ABL (Advanced Business Language)

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

by Federation

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

none

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.

User concepts

Access control

Access rights for users, groups and roles

Users and groups

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