DBMS > GeoMesa vs. Hypertable vs. RDF4J vs. Sequoiadb

System Properties Comparison GeoMesa vs. Hypertable vs. RDF4J vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

An open source BigTable implementation based on distributed file systems such as Hadoop

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

NewSQL database with distributed OLTP and SQL

Primary database model

Spatial DBMS

Wide column store

RDF store

Document store
Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

www.geomesa.org

rdf4j.org

www.sequoiadb.com

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

CCRi and others

Hypertable Inc.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Sequoiadb Ltd.

Initial release

2014

2009

2004

2013

Current release

5.0.0, May 2024

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU version 3. Commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

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

Scala

C++

Java

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

C++ API
Thrift

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor on file system level

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

simple password-based access control

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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