DBMS > EsgynDB vs. LevelDB vs. SpatiaLite

System Properties Comparison EsgynDB vs. LevelDB vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Spatial extension of SQLite

Primary database model

Relational DBMS

Key-value store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.esgyn.cn

github.com/google/leveldb

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Esgyn

Google

Alessandro Furieri

Initial release

2015

2011

2008

Current release

1.23, February 2021

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

server-less

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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