DBMS > EsgynDB vs. LeanXcale vs. Oracle Coherence vs. Postgres-XL

System Properties Comparison EsgynDB vs. LeanXcale vs. Oracle Coherence vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Oracles in-memory data grid solution

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

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

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

www.esgyn.cn

www.leanxcale.com

www.oracle.com/java/coherence

www.postgres-xl.org

Technical documentation

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

www.postgres-xl.org/documentation

Developer

Esgyn

LeanXcale

Oracle

Initial release

2015

2007

2014

since 2012, originally named StormDB

Current release

14.1, August 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

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

Server operating systems

Linux

All OS with a Java VM

Linux
macOS

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

yes

through Apache Derby

yes

distributed, parallel query execution

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JCache
JPA
RESTful HTTP API

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

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Scala

.Net
C++
Java

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

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

MVCC

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

fine grained access rights according to SQL-standard

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More resources

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