DBMS > EsgynDB vs. Oracle Coherence vs. OrientDB vs. Transwarp Hippo

System Properties Comparison EsgynDB vs. Oracle Coherence vs. OrientDB vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

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

Oracles in-memory data grid solution

Multi-model DBMS (Document, Graph, Key/Value)

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store

Vector DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

www.esgyn.cn

www.oracle.com/java/coherence

orientdb.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

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

www.orientdb.com/docs/last/index.html

Developer

Esgyn

Oracle

OrientDB LTD; CallidusCloud; SAP

Initial release

2015

2007

2010

2023

Current release

14.1, August 2023

3.2.29, March 2024

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

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

Java

C++

Server operating systems

Linux

All OS with a Java VM

All OS with a Java JDK (>= JDK 6)

Linux
macOS

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

SQL-like query language, no joins

APIs and other access methods

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C++
Java

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java, Javascript

Triggers

yes

Live Events

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes, with selectable consistency level

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

Access rights for users and roles; record level security configurable

Role based access control and fine grained access rights

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