DBMS > EJDB vs. HyperSQL vs. LokiJS vs. Spark SQL vs. Yanza

System Properties Comparison EJDB vs. HyperSQL vs. LokiJS vs. Spark SQL vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

In-memory JavaScript DBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

Time Series DBMS for IoT Applications

Primary database model

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

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Score	0.48
Rank	#262	Overall
	#42	Document stores

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

github.com/Softmotions/ejdb

hsqldb.org

github.com/techfort/LokiJS

spark.apache.org/sql

yanza.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

hsqldb.org/web/hsqlDocsFrame.html

techfort.github.io/LokiJS

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Softmotions

Apache Software Foundation

Yanza

Initial release

2012

2001

2014

2015

Current release

2.7.2, June 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

GPLv2

Open Source

based on BSD license

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

Scala

Server operating systems

server-less

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

via views

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

in-process shared library

HTTP API

JDBC via HTTP
JDBC
ODBC

JavaScript API

JDBC
ODBC

HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

All languages supporting JDBC/ODBC
Java

JavaScript

Java
Python
R
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

Java, SQL

View functions in JavaScript

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

fine grained access rights according to SQL-standard

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More resources

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