DBMS > Cubrid vs. Elasticsearch vs. HugeGraph vs. Splunk

System Properties Comparison Cubrid vs. Elasticsearch vs. HugeGraph vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A fast-speed and highly-scalable Graph DBMS

Analytics Platform for Big Data

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

cubrid.com (korean)
cubrid.org (english)

www.elastic.co/elasticsearch

github.com/hugegraph
hugegraph.apache.org

www.splunk.com

Technical documentation

cubrid.org/manuals

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

hugegraph.apache.org/docs

docs.splunk.com/Documentation/Splunk

Developer

CUBRID Corporation, CUBRID Foundation

Elastic

Baidu

Splunk Inc.

Initial release

2008

2010

2018

2003

Current release

11.0, January 2021

8.6, January 2023

0.9

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Elastic License

Open Source

Apache Version 2.0

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, C++, Java

Java

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
macOS
Unix

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP REST

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Groovy
Java
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

asynchronous Gremlin script jobs

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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.

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

Access rights for users and roles

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More resources

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