DBMS > Elasticsearch vs. gStore vs. Kinetica vs. MySQL vs. Trafodion

System Properties Comparison Elasticsearch vs. gStore vs. Kinetica vs. MySQL vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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 native Graph DBMS to store and maintain very large RDF datasets.

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Search engine

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.elastic.co/elasticsearch

Technical documentation

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

en.gstore.cn/#/enDocs

docs.kinetica.com

dev.mysql.com/doc

trafodion.apache.org/documentation.html

Developer

Elastic

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation, originally developed by HP

Initial release

2010

2016

2012

1995

2014

Current release

8.6, January 2023

1.2, November 2023

7.1, August 2021

8.4.0, April 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Elastic License

Open Source

BSD

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C, C++

C and C++

C++, Java

Server operating systems

All OS with a Java VM

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

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

schema-free and OWL/RDFS-schema support

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

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP API
SPARQL 1.1

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C++
Java
JavaScript (Node.js)
PHP
Python

C++
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions

yes

proprietary syntax

Java Stored Procedures

Triggers

yes

by using the 'percolation' feature

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

GPU vRAM or System RAM

yes

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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