DBMS > Ehcache vs. Hive vs. PostGIS vs. StarRocks

System Properties Comparison Ehcache vs. Hive vs. PostGIS vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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

Spatial extension of PostgreSQL

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Secondary database models

Relational DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

Technical documentation

www.ehcache.org/documentation

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

postgis.net/documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Terracotta Inc, owned by Software AG

Apache Software Foundation

initially developed by Facebook

The Linux Foundation

since Feb 2023

Initial release

2009

2012

2005

2020

Current release

3.10.0, March 2022

3.1.3, April 2022

3.4.2, February 2024

2.5.3, March 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2

Open Source

GPL v2.0

Open Source

Apache Version 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++, Java

Server operating systems

All OS with a Java VM

Linux

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JCache

JDBC
ODBC
Thrift

JDBC
MySQL protocol

Supported programming languages

Java

C++
Java
PHP
Python

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

yes

based on PostgreSQL

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

selectable replication factor

yes

based on PostgreSQL

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

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

based on PostgreSQL

Role based access control and fine grained access rights

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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