DBMS > EJDB vs. HyperSQL vs. LokiJS vs. Solr vs. Yanza

System Properties Comparison EJDB vs. HyperSQL vs. LokiJS vs. Solr 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

A widely used distributed, scalable search engine based on Apache Lucene

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

github.com/Softmotions/ejdb

hsqldb.org

github.com/techfort/LokiJS

solr.apache.org

yanza.com

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

techfort.github.io/LokiJS

solr.apache.org/resources.html

Developer

Softmotions

Apache Software Foundation

Yanza

Initial release

2012

2001

2014

2006

2015

Current release

2.7.2, June 2023

9.6.0, April 2024

License

Commercial or Open Source

Open Source

GPLv2

Open Source

based on BSD license

Open Source

Apache Version 2

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

Java

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)

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Windows

Data scheme

schema-free

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

APIs and other access methods

in-process shared library

HTTP API

JDBC via HTTP
JDBC
ODBC

JavaScript API

Java API
RESTful HTTP/JSON API

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

Java, SQL

View functions in JavaScript

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

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

optimistic locking

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

yes

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