DBMS > H2GIS vs. Hive vs. Sadas Engine vs. WakandaDB

System Properties Comparison H2GIS vs. Hive vs. Sadas Engine vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

data warehouse software for querying and managing large distributed datasets, built on Hadoop

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Spatial DBMS

Relational DBMS

Object oriented DBMS

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

www.h2gis.org/docs/home

cwiki.apache.org/confluence/display/Hive/Home

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

wakanda.github.io/doc

Developer

CNRS

Apache Software Foundation

initially developed by Facebook

SADAS s.r.l.

Wakanda SAS

Initial release

2013

2012

2006

2012

Current release

3.1.3, April 2022

8.0

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

Apache Version 2

commercial

free trial version available

Open Source

AGPLv3, extended commercial license available

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.

Implementation language

Java

C++

C++, JavaScript

Server operating systems

All OS with a Java VM

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

Supported programming languages

Java

C++
Java
PHP
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

based on H2

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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, 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

managed by 'Learn by Usage'

User concepts

Access control

yes

based on H2

Access rights for users, groups and roles

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

yes

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More resources

DB-Engines blog posts

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