DBMS > EsgynDB vs. GBase vs. Splunk

System Properties Comparison EsgynDB vs. GBase vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Analytics Platform for Big Data

Primary database model

Relational DBMS

Search engine

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

www.esgyn.cn

www.gbase.cn

www.splunk.com

Technical documentation

docs.splunk.com/Documentation/Splunk

Developer

Esgyn

General Data Technology Co., Ltd.

Splunk Inc.

Initial release

2015

2004

2003

Current release

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

commercial

Limited free edition and free developer edition available

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, Java, Python

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Data scheme

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

yes

Standard with numerous extensions

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Multi-source replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

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More resources

DB-Engines blog posts

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2 July 2014, Paul Andlinger

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