DBMS > LokiJS vs. MySQL vs. PostGIS vs. Splice Machine vs. Trafodion

System Properties Comparison LokiJS vs. MySQL vs. PostGIS vs. Splice Machine 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

In-memory JavaScript DBMS

Widely used open source RDBMS

Spatial extension of PostgreSQL

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

github.com/techfort/LokiJS

Technical documentation

techfort.github.io/LokiJS

dev.mysql.com/doc

postgis.net/documentation

splicemachine.com/how-it-works

trafodion.apache.org/documentation.html

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Splice Machine

Apache Software Foundation, originally developed by HP

Initial release

2014

1995

2005

2014

Current release

8.4.0, April 2024

3.4.2, February 2024

3.1, March 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL v2.0

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

JavaScript

C and C++

Java

C++, Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

JavaScript

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax

user defined functions

yes

Java

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

based on PostgreSQL

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

based on PostgreSQL

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

atomic operations within a single collection possible

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Users with fine-grained authorization concept

no user groups or roles

yes

based on PostgreSQL

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.