DBMS > EsgynDB vs. HEAVY.AI vs. Oracle Coherence vs. OushuDB vs. SpatiaLite

System Properties Comparison EsgynDB vs. HEAVY.AI vs. Oracle Coherence vs. OushuDB vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Oracles in-memory data grid solution

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Spatial extension of SQLite

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

www.esgyn.cn

github.com/heavyai/heavydb
www.heavy.ai

www.oracle.com/java/coherence

www.oushu.com/product/oushuDB

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.heavy.ai

docs.oracle.com/en/middleware/standalone/coherence

www.oushu.com/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Esgyn

HEAVY.AI, Inc.

Oracle

Oushu

Alessandro Furieri

Initial release

2015

2016

2007

2008

Current release

5.10, January 2022

14.1, August 2023

4.0.1, August 2020

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

C++, Java

C++ and CUDA

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux

server-less

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C++
Java

C
C++

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

Kerberos, SSL and role based access

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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