DBMS > EJDB vs. H2GIS vs. LeanXcale vs. Yanza

System Properties Comparison EJDB vs. H2GIS vs. LeanXcale vs. Yanza

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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)

Spatial extension of H2

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Time Series DBMS for IoT Applications

Primary database model

Document store

Spatial DBMS

Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Website

github.com/Softmotions/ejdb

www.h2gis.org

www.leanxcale.com

yanza.com

Technical documentation

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

www.h2gis.org/docs/home

Developer

Softmotions

CNRS

LeanXcale

Yanza

Initial release

2012

2013

2015

License

Commercial or Open Source

Open Source

GPLv2

Open Source

LGPL 3.0

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

Server operating systems

server-less

Windows

Data scheme

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

SQL

Support of SQL

yes

through Apache Derby

APIs and other access methods

in-process shared library

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP API

Supported programming languages

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

Java

C
Java
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

based on H2

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

yes

based on H2

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